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2403.12034 | 2024-03-19 | VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Models | [
"Junlin Han",
"Filippos Kokkinos",
"Philip Torr"
] | https://github.com/3DTopia/OpenLRM | null | 6 | 2 | 6 | 2024-03-19 | 4 | 4 | 4 | 5 | 0 | 5 | true | 2024-W12 | 2024-03 | false | 13 | 13 | 64 | 67 | 205 | 218 | This paper presents a novel paradigm for building scalable 3D generative
models utilizing pre-trained video diffusion models. The primary obstacle in
developing foundation 3D generative models is the limited availability of 3D
data. Unlike images, texts, or videos, 3D data are not readily accessible and
are difficult t... | [
{
"name": "Junlin Han",
"user": "JunlinHan",
"fullname": "Junlin Han",
"avatar": "/avatars/08683e07d89562f2fb5319854b21706c.svg",
"status": "extracted_pending",
"hidden": false
},
{
"name": "Filippos Kokkinos",
"user": "fkokkinos",
"fullname": "Filippos",
"avatar": "/avat... | null | null | null | akhaliq | AK | null | 2024-03-18T17:59:12.000Z | false | ||
2510.07172 | 2025-10-10 | NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents | [
"Tianshi Zheng",
"Kelvin Kiu-Wai Tam",
"Newt Hue-Nam K. Nguyen",
"Baixuan Xu",
"Zhaowei Wang",
"Jiayang Cheng",
"Hong Ting Tsang",
"Weiqi Wang",
"Jiaxin Bai",
"Tianqing Fang",
"Yangqiu Song",
"Ginny Y. Wong",
"Simon See"
] | https://github.com/HKUST-KnowComp/NewtonBench | null | 27 | 2 | 28 | 2025-10-10 | 25 | 27 | 27 | 27 | 1 | 27 | true | 2025-W41 | 2025-10 | false | 15 | 50 | 41 | 224 | 200 | 945 | Large language models are emerging as powerful tools for scientific law
discovery, a foundational challenge in AI-driven science. However, existing
benchmarks for this task suffer from a fundamental methodological trilemma,
forcing a trade-off between scientific relevance, scalability, and resistance
to memorization. F... | [
{
"name": "Tianshi Zheng",
"user": "StoneTZHENG",
"fullname": "Tianshi ZHENG",
"avatar": "/avatars/1e4e174c425943b7dde29c140d322478.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Kelvin Kiu-Wai Tam",
"user": null,
"fullname": null,
"avatar": null,
"... | null | null | null | tqfang229 | Tianqing Fang | /avatars/d4bc67c160a07146cf41c614678aa36b.svg | 158 | 2025-10-08T16:12:11.000Z | true | |
2508.15361 | 2025-08-22 | A Survey on Large Language Model Benchmarks | [
"Shiwen Ni",
"Guhong Chen",
"Shuaimin Li",
"Xuanang Chen",
"Siyi Li",
"Bingli Wang",
"Qiyao Wang",
"Xingjian Wang",
"Yifan Zhang",
"Liyang Fan",
"Chengming Li",
"Ruifeng Xu",
"Le Sun",
"Min Yang"
] | null | null | 19 | 2 | 20 | 2025-08-22 | 7 | 11 | 18 | 18 | 0 | 18 | true | 2025-W34 | 2025-08 | false | 6 | 16 | 35 | 95 | 159 | 452 | In recent years, with the rapid development of the depth and breadth of large
language models' capabilities, various corresponding evaluation benchmarks have
been emerging in increasing numbers. As a quantitative assessment tool for
model performance, benchmarks are not only a core means to measure model
capabilities b... | [
{
"name": "Shiwen Ni",
"user": "ShiwenNi",
"fullname": "ShiwenNi",
"avatar": "/avatars/a2f88017f7ab0cbea6862201e35fe747.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Guhong Chen",
"user": "youzi517",
"fullname": "Guhong Chen",
"avatar": "/avatars/5356e65... | null | null | null | taesiri | taesiri | null | 2025-08-21T08:43:35.000Z | false | ||
2512.05000 | 2025-12-05 | Reflection Removal through Efficient Adaptation of Diffusion Transformers | [
"Daniyar Zakarin",
"Thiemo Wandel",
"Anton Obukhov",
"Dengxin Dai"
] | https://github.com/huawei-bayerlab/windowseat-reflection-removal | https://huggingface.co/spaces/huawei-bayerlab/windowseat-reflection-removal-web | 18 | 3 | 18 | 2025-12-06 | null | 9 | 13 | 14 | 0 | 14 | true | 2025-W49 | 2025-12 | false | 15 | 38 | 72 | 191 | 264 | 633 | We introduce a diffusion-transformer (DiT) framework for single-image reflection removal that leverages the generalization strengths of foundation diffusion models in the restoration setting. Rather than relying on task-specific architectures, we repurpose a pre-trained DiT-based foundation model by conditioning it on ... | [
{
"name": "Daniyar Zakarin",
"user": "daniyarzt",
"fullname": "Daniyar Zakarin",
"avatar": "/avatars/4e3119525dd14ac7f6ae4b1c0bc251ef.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Thiemo Wandel",
"user": "thiemo-wandel",
"fullname": "Thiemo Wandel",
"a... | huawei-bayerlab | HUAWEI Bayer Lab | toshas | Anton Obukhov | 141 | 2025-12-04T17:12:39.000Z | true | |||
2604.18845 | 2026-04-22 | Dual-View Training for Instruction-Following Information Retrieval | [
"Qingcheng Zeng",
"Puxuan Yu",
"Aman Mehta",
"Fuheng Zhao",
"Rajhans Samdani"
] | null | null | 12 | 2 | 13 | 2026-04-22 | 9 | 10 | 10 | 10 | 1 | 10 | true | 2026-W17 | 2026-04 | false | 16 | 37 | 69 | 166 | 346 | 707 | Instruction-following information retrieval (IF-IR) studies retrieval systems that must not only find documents relevant to a query, but also obey explicit user constraints such as required attributes, exclusions, or output preferences. However, most retrievers are trained primarily for semantic relevance and often fai... | [
{
"name": "Qingcheng Zeng",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Puxuan Yu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Aman Mehta",
"user": "am... | Snowflake | Snowflake | qcz | Qingcheng Zeng | /avatars/94b04545ed9d30bfe58691672a0b5618.svg | null | 2026-04-20T00:00:00.000Z | false | ||
2603.28767 | 2026-03-31 | Gen-Searcher: Reinforcing Agentic Search for Image Generation | [
"Kaituo Feng",
"Manyuan Zhang",
"Shuang Chen",
"Yunlong Lin",
"Kaixuan Fan",
"Yilei Jiang",
"Hongyu Li",
"Dian Zheng",
"Chenyang Wang",
"Xiangyu Yue"
] | https://github.com/tulerfeng/Gen-Searcher | https://gen-searcher.vercel.app/ | 54 | 4 | 58 | 2026-03-31 | 43 | 51 | 53 | 55 | 4 | 55 | true | 2026-W14 | 2026-03 | false | 3 | 35 | 20 | 168 | 69 | 745 | Recent image generation models have shown strong capabilities in generating high-fidelity and photorealistic images. However, they are fundamentally constrained by frozen internal knowledge, thus often failing on real-world scenarios that are knowledge-intensive or require up-to-date information. In this paper, we pres... | [
{
"name": "Kaituo Feng",
"user": "KaituoFeng",
"fullname": "Kaituo Feng",
"avatar": "/avatars/32466863c5554f20cb2775b138832ac3.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Manyuan Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": nul... | null | null | null | taesiri | taesiri | 400 | 2026-03-30T17:59:56.000Z | true | ||
2510.13800 | 2025-10-16 | Reasoning in Space via Grounding in the World | [
"Yiming Chen",
"Zekun Qi",
"Wenyao Zhang",
"Xin Jin",
"Li Zhang",
"Peidong Liu"
] | https://github.com/WU-CVGL/GS-Reasoner | https://yiming-cc.github.io/gs-reasoner/ | 15 | 2 | 15 | 2025-10-16 | 13 | 14 | 14 | 14 | 0 | 14 | true | 2025-W42 | 2025-10 | false | 15 | 43 | 82 | 244 | 354 | 945 | In this paper, we claim that 3D visual grounding is the cornerstone of
spatial reasoning and introduce the Grounded-Spatial Reasoner (GS-Reasoner) to
explore the effective spatial representations that bridge the gap between them.
Existing 3D LLMs suffer from the absence of a unified 3D representation capable
of jointly... | [
{
"name": "Yiming Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zekun Qi",
"user": "qizekun",
"fullname": "Zekun Qi",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/63c3e8abc7d7f4c63a515a02/npMHnV... | null | null | null | qizekun | Zekun Qi | 57 | 2025-10-15T17:58:08.000Z | true | ||
2411.00660 | 2024-11-04 | Physics in Next-token Prediction | [
"Hongjun An",
"Yiliang Song",
"Xuelong Li"
] | null | null | 14 | 3 | 14 | 2024-11-04 | 1 | 11 | 13 | 14 | 0 | 14 | true | 2024-W45 | 2024-11 | false | 6 | 19 | 37 | 76 | 128 | 285 | We discovered the underlying physics in Next-token Prediction (NTP). We
identified the law of information conservation within NTP and proposed the
First Law of Information Capacity (IC-1), demonstrating that the essence of
intelligence emergence in auto-regressive models is fundamentally a process of
information transf... | [
{
"name": "Hongjun An",
"user": "Coder-AN",
"fullname": "Hongjun An",
"avatar": "/avatars/4f889e82fed3aaff058bde7299b8d585.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Yiliang Song",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | Coder-AN | Hongjun An | /avatars/4f889e82fed3aaff058bde7299b8d585.svg | null | 2024-11-01T15:26:15.000Z | true | |
2410.17250 | 2024-10-23 | JMMMU: A Japanese Massive Multi-discipline Multimodal Understanding Benchmark for Culture-aware Evaluation | [
"Shota Onohara",
"Atsuyuki Miyai",
"Yuki Imajuku",
"Kazuki Egashira",
"Jeonghun Baek",
"Xiang Yue",
"Graham Neubig",
"Kiyoharu Aizawa"
] | null | null | 14 | 2 | 15 | 2024-10-23 | 7 | 10 | 12 | 12 | 0 | 12 | true | 2024-W43 | 2024-10 | false | 7 | 13 | 44 | 98 | 216 | 482 | Accelerating research on Large Multimodal Models (LMMs) in non-English
languages is crucial for enhancing user experiences across broader populations.
In this paper, we introduce JMMMU (Japanese MMMU), the first large-scale
Japanese benchmark designed to evaluate LMMs on expert-level tasks based on the
Japanese cultura... | [
{
"name": "Shota Onohara",
"user": "shtapm",
"fullname": "Shota Onohara",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64fa893f35a7fc7d4ff63321/Gibk2euroCPycBFmf5I_p.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Atsuyuki Miyai",
"user": "... | null | null | null | AtsuMiyai | Atsuyuki Miyai | null | 2024-10-22T17:59:56.000Z | true | ||
2603.09930 | 2026-03-16 | Fine-grained Motion Retrieval via Joint-Angle Motion Images and Token-Patch Late Interaction | [
"Yao Zhang",
"Zhuchenyang Liu",
"Yanlan He",
"Thomas Ploetz",
"Yu Xiao"
] | null | null | 0 | 2 | 0 | 2026-03-16 | 0 | 0 | 0 | 0 | 0 | 0 | true | 2026-W12 | 2026-03 | false | 29 | 31 | 186 | 194 | 720 | 745 | Text-motion retrieval aims to learn a semantically aligned latent space between natural language descriptions and 3D human motion skeleton sequences, enabling bidirectional search across the two modalities. Most existing methods use a dual-encoder framework that compresses motion and text into global embeddings, discar... | [
{
"name": "Yao Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Zhuchenyang Liu",
"user": "Ryenhails",
"fullname": "Zhuchenyang Liu",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/66425e128a30a66d9... | null | null | null | Ryenhails | Zhuchenyang Liu | null | 2026-03-10T17:26:42.000Z | true | ||
2606.07502 | 2026-06-08 | Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings | [
"Songhao Wu",
"Zhongxin Chen",
"Yuxuan Liu",
"Heng Cui",
"Cong Li",
"Rui Yan"
] | https://github.com/CentreChen/EmbFilter | null | 99 | 8 | 100 | 2026-06-08 | 69 | 74 | 87 | 91 | 1 | 91 | true | 2026-W24 | 2026-06 | false | 2 | 48 | 13 | 239 | 36 | 946 | Large language models exhibit impressive zero-shot capabilities across a wide range of downstream tasks. However, they struggle to function as off-the-shelf embedding models, leading to suboptimal performance on massive text embedding benchmarks. In this paper, we identify a potential cause underlying this deficiency. ... | [
{
"name": "Songhao Wu",
"user": "shwu",
"fullname": "Songhao Wu",
"avatar": "/avatars/17139f0b6e8092cf4c135028db03a7ff.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Zhongxin Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | shwu | Songhao Wu | /avatars/17139f0b6e8092cf4c135028db03a7ff.svg | 26 | 2026-06-05T00:00:00.000Z | true | |
2502.14767 | 2025-02-24 | Tree-of-Debate: Multi-Persona Debate Trees Elicit Critical Thinking for Scientific Comparative Analysis | [
"Priyanka Kargupta",
"Ishika Agarwal",
"Tal August",
"Jiawei Han"
] | https://github.com/pkargupta/tree-of-debate | null | 7 | 2 | 7 | 2025-02-24 | 4 | 4 | 4 | 4 | 0 | 4 | true | 2025-W09 | 2025-02 | false | 23 | 34 | 103 | 134 | 399 | 502 | With the exponential growth of research facilitated by modern technology and
improved accessibility, scientific discoveries have become increasingly
fragmented within and across fields. This makes it challenging to assess the
significance, novelty, incremental findings, and equivalent ideas between
related works, parti... | [
{
"name": "Priyanka Kargupta",
"user": "pkargupta",
"fullname": "Priyanka Kargupta",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6476ae4083d4fdaedddf405f/ViS5-L6bNTfP5Vg0ASbqM.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ishika Agarwal",
... | null | null | null | pkargupta | Priyanka Kargupta | 20 | 2025-02-20T17:43:40.000Z | true | ||
2312.16457 | 2023-12-29 | City-on-Web: Real-time Neural Rendering of Large-scale Scenes on the Web | [
"Kaiwen Song",
"Juyong Zhang"
] | https://github.com/USTC3DV/MERFStudio | null | 15 | 1 | 15 | 2024-03-12 | null | null | null | null | 0 | 15 | true | 2023-W52 | 2023-12 | true | 8 | 19 | 16 | 47 | 107 | 293 | NeRF has significantly advanced 3D scene reconstruction, capturing intricate
details across various environments. Existing methods have successfully
leveraged radiance field baking to facilitate real-time rendering of small
scenes. However, when applied to large-scale scenes, these techniques encounter
significant chal... | [
{
"name": "Kaiwen Song",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Juyong Zhang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
}
] | null | null | null | akhaliq | AK | 88 | 2023-12-27T08:00:47.000Z | false | ||
2509.11492 | 2025-09-16 | ClaimIQ at CheckThat! 2025: Comparing Prompted and Fine-Tuned Language Models for Verifying Numerical Claims | [
"Anirban Saha Anik",
"Md Fahimul Kabir Chowdhury",
"Andrew Wyckoff",
"Sagnik Ray Choudhury"
] | null | null | 2 | 2 | 2 | 2025-09-16 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2025-W38 | 2025-09 | false | 16 | 20 | 88 | 101 | 487 | 536 | This paper presents our system for Task 3 of the CLEF 2025 CheckThat! Lab,
which focuses on verifying numerical and temporal claims using retrieved
evidence. We explore two complementary approaches: zero-shot prompting with
instruction-tuned large language models (LLMs) and supervised fine-tuning using
parameter-effici... | [
{
"name": "Anirban Saha Anik",
"user": "AnirbanSaha",
"fullname": "Anirban Saha Anik",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/8Phf6PKNMLA9WNwc0P9wu.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Md Fahimul Kabir Chowdhury",
... | null | null | null | AnirbanSaha | Anirban Saha Anik | null | 2025-09-15T01:03:09.000Z | true | ||
2603.06014 | 2026-03-09 | EffectMaker: Unifying Reasoning and Generation for Customized Visual Effect Creation | [
"Shiyuan Yang",
"Ruihuang Li",
"Jiale Tao",
"Shuai Shao",
"Qinglin Lu",
"Jing Liao"
] | https://github.com/ysy31415/EffectMaker | https://effectmaker.github.io/ | 9 | 2 | 9 | 2026-03-09 | 3 | 7 | 8 | 9 | 0 | 9 | true | 2026-W11 | 2026-03 | false | 10 | 31 | 74 | 187 | 376 | 745 | Visual effects (VFX) are essential for enhancing the expressiveness and creativity of video content, yet producing high-quality effects typically requires expert knowledge and costly production pipelines. Existing AIGC systems face significant challenges in VFX generation due to the scarcity of effect-specific data and... | [
{
"name": "Shiyuan Yang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Ruihuang Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jiale Tao",
"user": null... | null | null | null | ysy31415926 | Shiyuan Yang | 42 | 2026-03-06T08:09:14.000Z | false | ||
2609.22086 | 2026-09-21 | Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic Design | [
"Hongyang Du",
"Lan Yan",
"Christian Flores",
"Asim Kadav"
] | null | null | 34 | 3 | 34 | 2026-09-21 | 22 | 25 | 33 | 34 | 0 | 34 | true | 2026-W39 | 2026-09 | false | 10 | 31 | 43 | 139 | 233 | 786 | Professional graphic design is a long-horizon agentic task in which structured, editable artifacts emerge from many interdependent actions, yet outcomes admit no reliable programmatic oracle. We introduce a continual adaptation framework in which a frozen frontier model operates professional design software through mor... | [
{
"name": "Hongyang Du",
"user": "Hongyang-Du",
"fullname": "Hongyang Du",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/667230de876f9f27d6b097ea/hhz4nfTUdAAMIPXw3A342.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Lan Yan",
"user": null,... | adobe | Adobe | Hongyang-Du | Hongyang Du | null | 2026-09-18T00:00:00.000Z | true | |||
2412.13795 | 2024-12-19 | Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN | [
"Pengxiang Li",
"Lu Yin",
"Shiwei Liu"
] | https://github.com/pixeli99/mixln | null | 20 | 2 | 20 | 2024-12-19 | 12 | 17 | 18 | 18 | 0 | 18 | true | 2024-W51 | 2024-12 | false | 7 | 22 | 32 | 98 | 130 | 392 | Large Language Models (LLMs) have achieved remarkable success, yet recent
findings reveal that their deeper layers often contribute minimally and can be
pruned without affecting overall performance. While some view this as an
opportunity for model compression, we identify it as a training shortfall
rooted in the widesp... | [
{
"name": "Pengxiang Li",
"user": "pengxiang",
"fullname": "Pengxiang Li",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/64245f2c089d5fae56b4549a/qUHFsL9Svwyj5BKpfMtaY.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Lu Yin",
"user": null,
... | null | null | null | pengxiang | Pengxiang Li | 30 | 2024-12-18T12:39:53.000Z | true | ||
2508.21066 | 2025-08-29 | OneReward: Unified Mask-Guided Image Generation via Multi-Task Human Preference Learning | [
"Yuan Gong",
"Xionghui Wang",
"Jie Wu",
"Shiyin Wang",
"Yitong Wang",
"Xinglong Wu"
] | https://github.com/bytedance/OneReward | https://one-reward.github.io/ | 13 | 4 | 14 | 2025-08-29 | 5 | 7 | 11 | 11 | 1 | 11 | true | 2025-W35 | 2025-08 | false | 10 | 19 | 55 | 104 | 220 | 452 | In this paper, we introduce OneReward, a unified reinforcement learning
framework that enhances the model's generative capabilities across multiple
tasks under different evaluation criteria using only One Reward model.
By employing a single vision-language model (VLM) as the generative reward
model, which can distingui... | [
{
"name": "Yuan Gong",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Xionghui Wang",
"user": "XionghuiWang",
"fullname": "Xionghui Wang",
"avatar": "/avatars/f02399e5149da269b394114b3ff43ef8.svg",
"status": "claimed_veri... | null | null | null | XionghuiWang | Xionghui Wang | /avatars/f02399e5149da269b394114b3ff43ef8.svg | 350 | 2025-08-28T17:59:46.000Z | true | |
2509.20358 | 2025-09-25 | PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation | [
"Chen Wang",
"Chuhao Chen",
"Yiming Huang",
"Zhiyang Dou",
"Yuan Liu",
"Jiatao Gu",
"Lingjie Liu"
] | https://github.com/cwchenwang/physctrl | https://cwchenwang.github.io/physctrl/ | 15 | 2 | 15 | 2025-09-25 | 4 | 7 | 9 | 10 | 0 | 10 | true | 2025-W39 | 2025-09 | false | 6 | 14 | 54 | 129 | 273 | 536 | Existing video generation models excel at producing photo-realistic videos
from text or images, but often lack physical plausibility and 3D
controllability. To overcome these limitations, we introduce PhysCtrl, a novel
framework for physics-grounded image-to-video generation with physical
parameters and force control. ... | [
{
"name": "Chen Wang",
"user": "chenwang",
"fullname": "Chen Wang",
"avatar": "/avatars/3983be5662aa28aefcb18deaf08d7cb1.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Chuhao Chen",
"user": "MorPhLingXD",
"fullname": "Chuhao Chen",
"avatar": "https://cd... | null | null | null | taesiri | taesiri | 132 | 2025-09-24T17:58:04.000Z | false | ||
2601.00705 | 2026-01-08 | RGS-SLAM: Robust Gaussian Splatting SLAM with One-Shot Dense Initialization | [
"Wei-Tse Cheng",
"Yen-Jen Chiou",
"Yuan-Fu Yang"
] | https://github.com/Breeze1124/RGS-SLAM | https://breeze1124.github.io/rgs-slam-project-page/ | 4 | 2 | 4 | 2026-01-08 | 0 | 3 | 3 | 3 | 0 | 3 | true | 2026-W02 | 2026-01 | false | 16 | 20 | 87 | 120 | 446 | 573 | We introduce RGS-SLAM, a robust Gaussian-splatting SLAM framework that replaces the residual-driven densification stage of GS-SLAM with a training-free correspondence-to-Gaussian initialization. Instead of progressively adding Gaussians as residuals reveal missing geometry, RGS-SLAM performs a one-shot triangulation of... | [
{
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},
{
"name": "Yen-Jen Chiou",
"user": "remiii25",
"fullname": "Remi Chiou",
"avatar": "https://cd... | NYCU | National Yang Ming Chiao Tung University | Breeze1124 | cheng | /avatars/0bec08666319ce623a669cdc17f8cca8.svg | 8 | 2025-12-28T03:45:57.000Z | true | ||
2602.04521 | 2026-02-11 | C-ΔΘ: Circuit-Restricted Weight Arithmetic for Selective Refusal | [
"Aditya Kasliwal",
"Pratinav Seth",
"Vinay Kumar Sankarapu"
] | null | null | 0 | 2 | 1 | 2026-02-11 | 1 | 1 | 1 | 1 | 1 | 1 | true | 2026-W07 | 2026-02 | false | 49 | 57 | 218 | 247 | 675 | 785 | Modern deployments require LLMs to enforce safety policies at scale, yet many controls rely on inference-time interventions that add recurring compute cost and serving complexity. Activation steering is widely used, but it requires runtime hooks and scales cost with the number of generations; conditional variants impro... | [
{
"name": "Aditya Kasliwal",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
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},
{
"name": "Pratinav Seth",
"user": "pratinavsetharya",
"fullname": "Pratinav Seth",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/66fce04d... | Lexsi | Lexsi Labs | pratinavsetharya | Pratinav Seth | null | 2026-02-04T13:10:52.000Z | true | |||
2509.19676 | 2025-09-26 | Thinking While Listening: Simple Test Time Scaling For Audio Classification | [
"Prateek Verma",
"Mert Pilanci"
] | null | null | 5 | 2 | 5 | 2025-09-26 | 3 | 3 | 3 | 3 | 0 | 3 | true | 2025-W39 | 2025-09 | false | 29 | 35 | 89 | 129 | 407 | 536 | We propose a framework that enables neural models to "think while listening"
to everyday sounds, thereby enhancing audio classification performance.
Motivated by recent advances in the reasoning capabilities of large language
models, we address two central questions: (i) how can thinking be incorporated
into existing a... | [
{
"name": "Prateek Verma",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Mert Pilanci",
"user": "pilanci",
"fullname": "Mert Pilanci",
"avatar": "/avatars/00d30606183f629407b19678d5c369ff.svg",
"status": "admin_assigned"... | null | null | null | prateekv | Prateek Verma | /avatars/c74045063e7c06cb7be0fa41ebb1d824.svg | null | 2025-09-24T01:17:24.000Z | false | |
2606.05160 | 2026-06-04 | GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors | [
"Tianyi Xie",
"Haotian Zhang",
"Jinhyung Park",
"Zi Wang",
"Bowen Wen",
"Jiefeng Li",
"Xueting Li",
"Qingwei Ben",
"Haoyang Weng",
"Yufei Ye",
"David Minor",
"Tingwu Wang",
"Chenfanfu Jiang",
"Sanja Fidler",
"Jan Kautz",
"Linxi Fan",
"Yuke Zhu",
"Zhengyi Luo",
"Umar Iqbal",
"Ye... | https://github.com/NVlabs/GRAIL | https://research.nvidia.com/labs/dair/grail/ | 9 | 1 | 10 | 2026-06-04 | 5 | 7 | 7 | 8 | 1 | 8 | true | 2026-W23 | 2026-06 | false | 23 | 54 | 134 | 280 | 480 | 946 | Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture are difficult to scale because each collection depends on physical setups, instrumented actors, and robot operation. We present GRAIL, a digi... | [
{
"name": "Tianyi Xie",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Haotian Zhang",
"user": "haotianz94",
"fullname": "Haotian Zhang",
"avatar": "/avatars/9c9a8c4a52e7f4c6ecd3984b375ec431.svg",
"status": "claimed_verif... | nvidia | NVIDIA | taesiri | taesiri | 554 | 2026-06-03T00:00:00.000Z | false | |||
2602.21374 | 2026-02-26 | Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages | [
"Mohammadreza Ghaffarzadeh-Esfahani",
"Nahid Yousefian",
"Ebrahim Heidari-Farsani",
"Ali Akbar Omidvarian",
"Sepehr Ghahraei",
"Atena Farangi",
"AmirBahador Boroumand"
] | https://github.com/mohammad-gh009/Small-language-models-on-clinical-data-extraction | null | 1 | 2 | 1 | 2026-02-26 | 1 | 1 | 1 | 1 | 0 | 1 | true | 2026-W09 | 2026-02 | false | 24 | 31 | 110 | 134 | 675 | 785 | Extracting clinical information from medical transcripts in low-resource languages remains a significant challenge in healthcare natural language processing (NLP). This study evaluates a two-step pipeline combining Aya-expanse-8B as a Persian-to-English translation model with five open-source small language models (SLM... | [
{
"name": "Mohammadreza Ghaffarzadeh-Esfahani",
"user": "Moreza009",
"fullname": "MoRezaGH",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/645d63c0ce72244df7b36be8/09vhYAzgv1svwvQM4eIE9.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Nahid You... | null | null | null | Moreza009 | MoRezaGH | 0 | 2026-02-24T21:10:29.000Z | true | ||
2605.00877 | 2026-05-05 | OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models | [
"Yida Xue",
"Ningyu Zhang",
"Tingwei Wu",
"Zhe Ma",
"Daxiong Ji",
"Zhao Wang",
"Guozhou Zheng",
"Huajun Chen"
] | https://github.com/OceanGPT/OceanPile | http://data.oceangpt.blue/en/ | 14 | 3 | 16 | 2026-05-11 | null | null | null | 15 | 2 | 15 | true | 2026-W19 | 2026-05 | false | 7 | 25 | 44 | 132 | 344 | 939 | The vast and underexplored ocean plays a critical role in regulating global climate and supporting marine biodiversity, yet artificial intelligence has so far delivered limited impact in this domain due to a fundamental data bottleneck. Specifically, ocean data are highly fragmented across disparate sources and inheren... | [
{
"name": "Yida Xue",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Ningyu Zhang",
"user": "Ningyu",
"fullname": "Ningyu Zhang",
"avatar": "/avatars/e0fccbb2577d76088e09f054c35cffbc.svg",
"status": "claimed_verified",
... | ZhejiangUniversity | Zhejiang University | https://www.gravatar.com/avatar/d1d414628877bec2958f95ad283c15e7?d=retro&size=100 | Ningyu | Ningyu Zhang | /avatars/e0fccbb2577d76088e09f054c35cffbc.svg | 12 | 2026-04-25T00:00:00.000Z | true | |
2502.12929 | 2025-02-19 | Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options | [
"Lakshmi Nair",
"Ian Trase",
"Mark Kim"
] | https://github.com/flagshippioneering/Flow-of-Options | null | 8 | 3 | 8 | 2025-02-19 | 4 | 6 | 6 | 7 | 0 | 7 | true | 2025-W08 | 2025-02 | false | 23 | 33 | 92 | 154 | 325 | 502 | We present a novel reasoning approach called Flow-of-Options (FoO), designed
to address intrinsic biases in Large Language Models (LLMs). FoO enables LLMs
to systematically explore a diverse range of possibilities in their reasoning,
as demonstrated by an FoO-based agentic system for autonomously solving Machine
Learni... | [
{
"name": "Lakshmi Nair",
"user": "lnair",
"fullname": "Lakshmi Nair",
"avatar": "/avatars/5b95d2509d1c7640d77a3405ebd53eaf.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ian Trase",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | lnair | Lakshmi Nair | /avatars/5b95d2509d1c7640d77a3405ebd53eaf.svg | 9 | 2025-02-18T15:11:46.000Z | true | |
2512.01342 | 2025-12-02 | InternVideo-Next: Towards General Video Foundation Models without Video-Text Supervision | [
"Chenting Wang",
"Yuhan Zhu",
"Yicheng Xu",
"Jiange Yang",
"Ziang Yan",
"Yali Wang",
"Yi Wang",
"Limin Wang"
] | null | null | 21 | 1 | 21 | 2025-12-02 | 14 | 14 | 14 | 14 | 0 | 14 | true | 2025-W49 | 2025-12 | false | 18 | 47 | 72 | 191 | 264 | 633 | Large-scale video-text pretraining achieves strong performance but depends on noisy, synthetic captions with limited semantic coverage, often overlooking implicit world knowledge such as object motion, 3D geometry, and physical cues. In contrast, masked video modeling (MVM) directly exploits spatiotemporal structures b... | [
{
"name": "Chenting Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yuhan Zhu",
"user": "ZhuYuhan",
"fullname": "Yuhan Zhu",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/61bda7dda3082b8d007d6195/5... | OpenGVLab | OpenGVLab | ynhe | yinanhe | null | 2025-12-01T06:57:39.000Z | false | |||
2510.16136 | 2025-10-21 | GuideFlow3D: Optimization-Guided Rectified Flow For Appearance Transfer | [
"Sayan Deb Sarkar",
"Sinisa Stekovic",
"Vincent Lepetit",
"Iro Armeni"
] | https://github.com/GradientSpaces/GuideFlow3D | https://sayands.github.io/guideflow3d/ | 5 | 2 | 5 | 2025-10-21 | 0 | 1 | 2 | 2 | 0 | 2 | true | 2025-W43 | 2025-10 | false | 28 | 36 | 143 | 166 | 756 | 945 | Transferring appearance to 3D assets using different representations of the
appearance object - such as images or text - has garnered interest due to its
wide range of applications in industries like gaming, augmented reality, and
digital content creation. However, state-of-the-art methods still fail when the
geometry ... | [
{
"name": "Sayan Deb Sarkar",
"user": "sayandsarkar",
"fullname": "Sayan Deb Sarkar",
"avatar": "/avatars/c26c03fa920d857120f03c9ccb9f1d7a.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Sinisa Stekovic",
"user": null,
"fullname": null,
"avatar": null,
... | gradient-spaces | Gradient Spaces Research Group | sayandsarkar | Sayan Deb Sarkar | /avatars/c26c03fa920d857120f03c9ccb9f1d7a.svg | 28 | 2025-10-17T18:22:04.000Z | true | ||
2609.32915 | 2026-09-30 | AgentTell: Behavioural Side-Channel Leakage in Browser-Use Agents | [
"Asif Shahriar",
"Md Nafiu Rahman",
"Sadif Ahmed",
"Farig Sadeque",
"Md Rizwan Parvez"
] | https://github.com/kagnlp/AgentTell | null | 2 | 2 | 2 | 2026-10-01 | null | 2 | 2 | 2 | 0 | 2 | true | 2026-W40 | 2026-09 | false | 91 | 92 | 374 | 404 | 756 | 786 | Browser-use agents often carry information in their context as they move between websites. While it may be necessary for task completion, it also creates a privacy risk, especially when the information contains a private fact regarding the user. For example, an agent may learn a user's affiliation after reading a membe... | [
{
"name": "Asif Shahriar",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Md Nafiu Rahman",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Sadif Ahmed",
"user... | kagnlp | Knowledge Augmented Generation (KAGNLP) | asif-shahriar11 | Asif Shahriar | /avatars/6aa29dfc15938ccef409e6e89ec4d7cc.svg | 1 | 2026-09-26T00:00:00.000Z | false | ||
2610.03978 | 2026-10-06 | Learning Latent Protein Languages for Autoregressive Generation | [
"Mahdi Pourmirzaei",
"Farzaneh Esmaili",
"Amir Ziashahabi",
"Mohammadreza Pourmirzaei",
"Dong Xu"
] | https://github.com/mahdip72/latent_protein_languages | https://mahdip72.github.io/latent-protein-languages.github.io/ | 5 | 1 | 5 | 2026-10-06 | 1 | 5 | 5 | 5 | 0 | 5 | false | 2026-W41 | 2026-10 | false | 58 | 81 | 129 | 169 | 260 | 339 | Autoregressive transformers remain comparatively weak for protein sequence and structure generation. We study the role of target representation: amino acid tokens encode residue identities without explicit contextual semantics, while backbone coordinates require a discrete representation in our framework. We introduce ... | [
{
"name": "Mahdi Pourmirzaei",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Farzaneh Esmaili",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Amir Ziashahabi",
... | null | null | null | Mahdip72 | Mahdi Pourmirzaei | /avatars/62879c8a8bbdbaaf63da27a44e90bd5f.svg | 0 | 2026-10-02T00:00:00.000Z | false | |
2606.05633 | 2026-06-09 | Answer Presence Drives RAG Rewriting Gains | [
"Yuejie Li",
"Yueying Hua",
"Ke Yang",
"Li Zhang",
"Yueping He",
"Yueping He",
"Ruiqi Li",
"Bolin Chen",
"Tao Wang",
"Bowen Li",
"Chengjun Mao"
] | null | null | 7 | 2 | 8 | 2026-06-09 | 7 | 7 | 8 | 8 | 1 | 8 | true | 2026-W24 | 2026-06 | false | 27 | 59 | 115 | 239 | 480 | 946 | Retrieval-augmented QA pipelines often route retrieved passages through an LLM rewriter before a smaller reader, lifting F1 by tens of points on multi-hop benchmarks; this gain is typically credited to improved evidence quality. We ask whether that lift is causally driven by the gold answer string appearing in the rewr... | [
{
"name": "Yuejie Li",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Yueying Hua",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Ke Yang",
"user": "TroyeML"... | null | null | null | TroyeML | ShinerYang | /avatars/4cfb641424e7510f2be8ec3945c86c39.svg | null | 2026-06-04T03:00:42.000Z | true | |
2509.15178 | 2025-09-19 | Unleashing the Potential of Multimodal LLMs for Zero-Shot Spatio-Temporal Video Grounding | [
"Zaiquan Yang",
"Yuhao Liu",
"Gerhard Hancke",
"Rynson W. H. Lau"
] | https://github.com/zaiquanyang/LLaVA_Next_STVG | null | 6 | 2 | 6 | 2025-09-19 | 3 | 4 | 5 | 5 | 0 | 5 | true | 2025-W38 | 2025-09 | false | 14 | 20 | 66 | 101 | 359 | 536 | Spatio-temporal video grounding (STVG) aims at localizing the spatio-temporal
tube of a video, as specified by the input text query. In this paper, we
utilize multimodal large language models (MLLMs) to explore a zero-shot
solution in STVG. We reveal two key insights about MLLMs: (1) MLLMs tend to
dynamically assign sp... | [
{
"name": "Zaiquan Yang",
"user": "zaiquan",
"fullname": "Zaiquan yang",
"avatar": "/avatars/05ac913fcf7d94d51b75a3fea87d6de2.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Yuhao Liu",
"user": "yuhaoliu",
"fullname": "yuhaoliu",
"avatar": "/avatars/36218f... | null | null | null | LeoLau | Yuhao Liu | /avatars/ec0e8f378d5314d4af97d6c488771b3d.svg | 21 | 2025-09-18T17:35:50.000Z | false | |
2311.10794 | 2023-11-21 | Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression | [
"Animesh Sinha",
"Bo Sun",
"Anmol Kalia",
"Arantxa Casanova",
"Elliot Blanchard",
"David Yan",
"Winnie Zhang",
"Tony Nelli",
"Jiahui Chen",
"Hardik Shah",
"Licheng Yu",
"Mitesh Kumar Singh",
"Ankit Ramchandani",
"Maziar Sanjabi",
"Sonal Gupta",
"Amy Bearman",
"Dhruv Mahajan"
] | null | null | 27 | 1 | 28 | 2024-03-12 | null | null | null | null | 0 | 27 | true | 2023-W47 | 2023-11 | true | 8 | 16 | 18 | 44 | 47 | 174 | We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models
(LDMs) in a distinct domain with high visual quality, prompt alignment and
scene diversity. We choose sticker image generation as the target domain, as
the images significantly differ from photorealistic samples typically generated
by large-scal... | [
{
"name": "Animesh Sinha",
"user": "animeshsinha",
"fullname": "Animesh Sinha",
"avatar": "/avatars/be71b00e009f2093a3ff79f07815e68e.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Bo Sun",
"user": "bsun0802",
"fullname": "Bo Sun",
"avatar": "https://cdn... | null | null | null | akhaliq | AK | null | 2023-11-17T03:00:29.000Z | false | ||
2509.19033 | 2025-09-30 | Charting a Decade of Computational Linguistics in Italy: The CLiC-it Corpus | [
"Chiara Alzetta",
"Serena Auriemma",
"Alessandro Bondielli",
"Luca Dini",
"Chiara Fazzone",
"Alessio Miaschi",
"Martina Miliani",
"Marta Sartor"
] | https://github.com/alemiaschi/clic-it_corpus | null | 2 | 1 | 2 | 2026-05-11 | null | null | null | null | 0 | 2 | true | 2025-W40 | 2025-09 | false | 70 | 82 | 219 | 275 | 445 | 536 | Over the past decade, Computational Linguistics (CL) and Natural Language
Processing (NLP) have evolved rapidly, especially with the advent of
Transformer-based Large Language Models (LLMs). This shift has transformed
research goals and priorities, from Lexical and Semantic Resources to Language
Modelling and Multimoda... | [
{
"name": "Chiara Alzetta",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Serena Auriemma",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Alessandro Bondielli",... | null | null | null | alemiaschi | Alessio Miaschi | 0 | 2025-09-23T14:06:09.000Z | false | ||
2408.02657 | 2024-08-06 | Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretraining | [
"Dongyang Liu",
"Shitian Zhao",
"Le Zhuo",
"Weifeng Lin",
"Yu Qiao",
"Hongsheng Li",
"Peng Gao"
] | https://github.com/alpha-vllm/lumina-mgpt | null | 34 | 2 | 36 | 2024-08-06 | 21 | 24 | 27 | 29 | 2 | 29 | true | 2024-W32 | 2024-08 | false | 2 | 14 | 8 | 58 | 53 | 271 | We present Lumina-mGPT, a family of multimodal autoregressive models capable
of various vision and language tasks, particularly excelling in generating
flexible photorealistic images from text descriptions. Unlike existing
autoregressive image generation approaches, Lumina-mGPT employs a pretrained
decoder-only transfo... | [
{
"name": "Dongyang Liu",
"user": "Cxxs",
"fullname": "Dongyang Liu (Chris Liu)",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/646f1bef075e11ca78da3bb7/gNS-ikyZXYeMrf4a7HTQE.jpeg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Shitian Zhao",
"us... | null | null | null | akhaliq | AK | 648 | 2024-08-05T17:46:53.000Z | false | ||
2512.05409 | 2025-12-08 | SQ-format: A Unified Sparse-Quantized Hardware-friendly Data Format for LLMs | [
"Ruixuan Huang",
"Hao Zeng",
"Hantao Huang",
"Jinyuan Shi",
"Minghui Yu",
"Ian En-Hsu Yen",
"Shuai Wang"
] | null | null | 4 | 2 | 4 | 2025-12-08 | 2 | 2 | 2 | 2 | 0 | 2 | true | 2025-W50 | 2025-12 | false | 21 | 24 | 107 | 130 | 525 | 633 | Post-training quantization (PTQ) plays a crucial role in the democratization of large language models (LLMs). However, existing low-bit quantization and sparsification techniques are difficult to balance accuracy and efficiency due to the limited hardware support. For example, W4A8 can only achieve the same peak TOPS a... | [
{
"name": "Ruixuan Huang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Hao Zeng",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Hantao Huang",
"user": nul... | null | null | null | HRXUST | Sprout Huang | null | 2025-12-05T03:58:04.000Z | false | ||
2505.20715 | 2025-05-29 | MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding | [
"Fuwen Luo",
"Shengfeng Lou",
"Chi Chen",
"Ziyue Wang",
"Chenliang Li",
"Weizhou Shen",
"Jiyue Guo",
"Peng Li",
"Ming Yan",
"Ji Zhang",
"Fei Huang",
"Yang Liu"
] | https://github.com/THUNLP-MT/MUSEG | null | 2 | 2 | 2 | 2025-05-29 | 2 | 2 | 2 | 2 | 0 | 2 | true | 2025-W22 | 2025-05 | false | 50 | 58 | 269 | 318 | 634 | 730 | Video temporal understanding is crucial for multimodal large language models
(MLLMs) to reason over events in videos. Despite recent advances in general
video understanding, current MLLMs still struggle with fine-grained temporal
reasoning. While reinforcement learning (RL) has been explored to address this
issue recen... | [
{
"name": "Fuwen Luo",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Shengfeng Lou",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Chi Chen",
"user": null,
... | null | null | null | carboncoo | Chi Chen | /avatars/915a4d7b89455ae97b8544c79286ddf8.svg | 39 | 2025-05-27T04:50:07.000Z | false | |
2602.10999 | 2026-02-12 | CLI-Gym: Scalable CLI Task Generation via Agentic Environment Inversion | [
"Yusong Lin",
"Haiyang Wang",
"Shuzhe Wu",
"Lue Fan",
"Feiyang Pan",
"Sanyuan Zhao",
"Dandan Tu"
] | https://github.com/LiberCoders/CLI-Gym | null | 11 | 1 | 11 | 2026-02-12 | 10 | 10 | 10 | 10 | 0 | 10 | true | 2026-W07 | 2026-02 | false | 24 | 48 | 118 | 247 | 353 | 785 | Agentic coding requires agents to effectively interact with runtime environments, e.g., command line interfaces (CLI), so as to complete tasks like resolving dependency issues, fixing system problems, etc. But it remains underexplored how such environment-intensive tasks can be obtained at scale to enhance agents' capa... | [
{
"name": "Yusong Lin",
"user": "x1aoche",
"fullname": "Yusong Lin",
"avatar": "/avatars/a1ec00149303e4c69e43821d2ee43218.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Haiyang Wang",
"user": "Haiyang-W",
"fullname": "Haiyang Wang",
"avatar": "/avatars/... | null | null | null | taesiri | taesiri | 141 | 2026-02-11T16:22:18.000Z | false | ||
2305.16355 | 2023-05-29 | PandaGPT: One Model To Instruction-Follow Them All | [
"Yixuan Su",
"Tian Lan",
"Huayang Li",
"Jialu Xu",
"Yan Wang",
"Deng Cai"
] | https://github.com/yxuansu/pandagpt | null | 4 | 1 | 4 | 2024-03-12 | null | null | null | null | 0 | 4 | true | 2023-W22 | 2023-05 | true | 5 | 21 | 32 | 86 | 75 | 258 | We present PandaGPT, an approach to emPower large lANguage moDels with visual
and Auditory instruction-following capabilities. Our pilot experiments show
that PandaGPT can perform complex tasks such as detailed image description
generation, writing stories inspired by videos, and answering questions about
audios. More ... | [
{
"name": "Yixuan Su",
"user": "pangpang666",
"fullname": "Yixuan Su",
"avatar": "/avatars/1f9bbb70f859f34563fdd0a7de4cd254.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Tian Lan",
"user": "GMFTBY",
"fullname": "Tian Lan",
"avatar": "https://cdn-avatar... | null | null | null | akhaliq | AK | 865 | 2023-05-25T04:16:07.000Z | false | ||
2404.02078 | 2024-04-03 | Advancing LLM Reasoning Generalists with Preference Trees | [
"Lifan Yuan",
"Ganqu Cui",
"Hanbin Wang",
"Ning Ding",
"Xingyao Wang",
"Jia Deng",
"Boji Shan",
"Huimin Chen",
"Ruobing Xie",
"Yankai Lin",
"Zhenghao Liu",
"Bowen Zhou",
"Hao Peng",
"Zhiyuan Liu",
"Maosong Sun"
] | https://github.com/openbmb/eurus | null | 45 | 2 | 47 | 2024-04-03 | 28 | 32 | 34 | 36 | 2 | 36 | true | 2024-W14 | 2024-04 | false | 2 | 11 | 9 | 51 | 28 | 199 | We introduce Eurus, a suite of large language models (LLMs) optimized for
reasoning. Finetuned from Mistral-7B and CodeLlama-70B, Eurus models achieve
state-of-the-art results among open-source models on a diverse set of
benchmarks covering mathematics, code generation, and logical reasoning
problems. Notably, Eurus-70... | [
{
"name": "Lifan Yuan",
"user": "lievan",
"fullname": "Lifan",
"avatar": "/avatars/21301cd9929a1a64f3f6427413855ea8.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Ganqu Cui",
"user": "ganqu",
"fullname": "Ganqu Cui",
"avatar": "/avatars/af6f5ee78f161d25... | null | null | null | akhaliq | AK | 323 | 2024-04-02T16:25:30.000Z | false | ||
2410.06555 | 2024-10-10 | ING-VP: MLLMs cannot Play Easy Vision-based Games Yet | [
"Haoran Zhang",
"Hangyu Guo",
"Shuyue Guo",
"Meng Cao",
"Wenhao Huang",
"Jiaheng Liu",
"Ge Zhang"
] | https://github.com/thisisus7/ing-vp | null | 8 | 2 | 8 | 2024-10-10 | 6 | 7 | 8 | 8 | 0 | 8 | true | 2024-W41 | 2024-10 | false | 26 | 49 | 69 | 126 | 277 | 482 | As multimodal large language models (MLLMs) continue to demonstrate
increasingly competitive performance across a broad spectrum of tasks, more
intricate and comprehensive benchmarks have been developed to assess these
cutting-edge models. These benchmarks introduce new challenges to core
capabilities such as perceptio... | [
{
"name": "Haoran Zhang",
"user": "RickStark",
"fullname": "Haoran Zhang",
"avatar": "/avatars/b039807814f5a778ca327ead232fc67b.svg",
"status": "extracted_pending",
"hidden": false
},
{
"name": "Hangyu Guo",
"user": "Rosiness",
"fullname": "hangyu guo",
"avatar": "/avatar... | null | null | null | Rosiness | hangyu guo | /avatars/cf791574ab986bac274e7fbcf04e2a59.svg | 14 | 2024-10-09T05:17:38.000Z | true | |
2503.03044 | 2025-03-06 | QE4PE: Word-level Quality Estimation for Human Post-Editing | [
"Gabriele Sarti",
"Vilém Zouhar",
"Grzegorz Chrupała",
"Ana Guerberof-Arenas",
"Malvina Nissim",
"Arianna Bisazza"
] | https://github.com/gsarti/qe4pe | https://gsarti.com/publication/qe4pe | 5 | 2 | 6 | 2025-03-06 | 5 | 5 | 5 | 6 | 1 | 6 | true | 2025-W10 | 2025-03 | false | 11 | 21 | 78 | 114 | 399 | 611 | Word-level quality estimation (QE) detects erroneous spans in machine
translations, which can direct and facilitate human post-editing. While the
accuracy of word-level QE systems has been assessed extensively, their
usability and downstream influence on the speed, quality and editing choices of
human post-editing rema... | [
{
"name": "Gabriele Sarti",
"user": "gsarti",
"fullname": "Gabriele Sarti",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/5e7749883d77a72421292d07/M4AmBReZk_otxCIG3o0bL.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Vilém Zouhar",
"user":... | null | null | null | gsarti | Gabriele Sarti | 5 | 2025-03-04T22:50:17.000Z | true | ||
2309.02186 | 2023-09-06 | AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections | [
"Yue Wu",
"Sicheng Xu",
"Jianfeng Xiang",
"Fangyun Wei",
"Qifeng Chen",
"Jiaolong Yang",
"Xin Tong"
] | null | null | 23 | 3 | 23 | 2024-03-12 | null | null | null | null | 0 | 23 | true | 2023-W36 | 2023-09 | true | 2 | 15 | 10 | 42 | 57 | 185 | Previous animatable 3D-aware GANs for human generation have primarily focused
on either the human head or full body. However, head-only videos are relatively
uncommon in real life, and full body generation typically does not deal with
facial expression control and still has challenges in generating high-quality
results... | [
{
"name": "Yue Wu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Sicheng Xu",
"user": "sicxu",
"fullname": "Sicheng Xu",
"avatar": "/avatars/d1a7297ca7d4cdbbe484a54d7d223551.svg",
"status": "claimed_verified",
"hidd... | null | null | null | akhaliq | AK | null | 2023-09-05T12:44:57.000Z | false | ||
2512.17220 | 2025-12-29 | Mindscape-Aware Retrieval Augmented Generation for Improved Long Context Understanding | [
"Yuqing Li",
"Jiangnan Li",
"Zheng Lin",
"Ziyan Zhou",
"Junjie Wu",
"Weiping Wang",
"Jie Zhou",
"Mo Yu"
] | null | null | 114 | 3 | 115 | 2025-12-29 | 69 | 85 | 89 | 108 | 1 | 108 | true | 2026-W01 | 2025-12 | false | 1 | 15 | 3 | 80 | 13 | 633 | Humans understand long and complex texts by relying on a holistic semantic representation of the content. This global view helps organize prior knowledge, interpret new information, and integrate evidence dispersed across a document, as revealed by the Mindscape-Aware Capability of humans in psychology. Current Retriev... | [
{
"name": "Yuqing Li",
"user": "MindscapeRAG",
"fullname": "Yuqing Li",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/6891bbff78946201296b4592/ECmWBrlfeonPg0HzmQ_sW.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Jiangnan Li",
"user": "loss... | tencent | Tencent | BishopGorov | Mo | /avatars/8bad9272fe73ba04e077b5484837c8d3.svg | null | 2025-12-19T04:08:29.000Z | true | ||
2605.18746 | 2026-05-20 | ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop | [
"Yining Hong",
"Jiageng Liu",
"Han Yin",
"Manling Li",
"Leonidas Guibas",
"Li Fei-Fei",
"Jiajun Wu",
"Yejin Choi"
] | https://github.com/ESI-Bench/ESI-Bench | https://esi-bench.github.io/ | 7 | 1 | 8 | 2026-05-20 | 3 | 4 | 5 | 5 | 1 | 5 | true | 2026-W21 | 2026-05 | false | 35 | 54 | 163 | 238 | 641 | 939 | Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a function of action. Rather than passively processing what is seen, they actively uncover what is unseen - occluded structure, dynamics, containment, and functionality that canno... | [
{
"name": "Yining Hong",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jiageng Liu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Han Yin",
"user": null,
... | null | null | null | evelynhong | Yining Hong | /avatars/ea577762b6b4798f87a7a3f1d53d082c.svg | 134 | 2026-05-18T00:00:00.000Z | false | |
2505.17540 | 2025-05-26 | RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning | [
"Mingrui Wu",
"Lu Wang",
"Pu Zhao",
"Fangkai Yang",
"Jianjin Zhang",
"Jianfeng Liu",
"Yuefeng Zhan",
"Weihao Han",
"Hao Sun",
"Jiayi Ji",
"Xiaoshuai Sun",
"Qingwei Lin",
"Weiwei Deng",
"Dongmei Zhang",
"Feng Sun",
"Qi Zhang",
"Rongrong Ji"
] | https://github.com/microsoft/DKI_LLM | null | 7 | 2 | 7 | 2025-05-26 | 5 | 5 | 7 | 7 | 0 | 7 | true | 2025-W22 | 2025-05 | false | 30 | 47 | 176 | 318 | 439 | 730 | Despite recent progress in text-to-image (T2I) generation, existing models
often struggle to faithfully capture user intentions from short and
under-specified prompts. While prior work has attempted to enhance prompts
using large language models (LLMs), these methods frequently generate stylistic
or unrealistic content... | [
{
"name": "Mingrui Wu",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Lu Wang",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Pu Zhao",
"user": null,
"f... | null | null | null | mrwu | Mingrui Wu | /avatars/2d99114e5cff39dccc385adfad7032c5.svg | 40 | 2025-05-23T06:44:26.000Z | false | |
2403.13799 | 2024-03-21 | Reverse Training to Nurse the Reversal Curse | [
"Olga Golovneva",
"Zeyuan Allen-Zhu",
"Jason Weston",
"Sainbayar Sukhbaatar"
] | null | null | 13 | 1 | 13 | 2024-03-21 | 7 | 8 | 9 | 10 | 0 | 10 | true | 2024-W12 | 2024-03 | false | 13 | 18 | 42 | 67 | 146 | 218 | Large language models (LLMs) have a surprising failure: when trained on "A
has a feature B", they do not generalize to "B is a feature of A", which is
termed the Reversal Curse. Even when training with trillions of tokens this
issue still appears due to Zipf's law - hence even if we train on the entire
internet. This w... | [
{
"name": "Olga Golovneva",
"user": "Golovneva",
"fullname": "Olga Golovneva",
"avatar": "/avatars/2d9f96eb4092a9d1734dcc09303b259a.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Zeyuan Allen-Zhu",
"user": "zhuzeyuan",
"fullname": "Zeyuan Allen-Zhu",
"ava... | null | null | null | akhaliq | AK | null | 2024-03-20T17:55:35.000Z | false | ||
2507.01955 | 2025-07-07 | How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks | [
"Rahul Ramachandran",
"Ali Garjani",
"Roman Bachmann",
"Andrei Atanov",
"Oğuzhan Fatih Kar",
"Amir Zamir"
] | https://github.com/EPFL-VILAB/fm-vision-evals | https://fm-vision-evals.epfl.ch/ | 36 | 2 | 36 | 2025-07-07 | 9 | 24 | 29 | 33 | 0 | 33 | true | 2025-W28 | 2025-07 | false | 1 | 4 | 22 | 99 | 97 | 383 | Multimodal foundation models, such as GPT-4o, have recently made remarkable
progress, but it is not clear where exactly these models stand in terms of
understanding vision. In this paper, we benchmark the performance of popular
multimodal foundation models (GPT-4o, o4-mini, Gemini 1.5 Pro and Gemini 2.0
Flash, Claude 3... | [
{
"name": "Rahul Ramachandran",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Ali Garjani",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Roman Bachmann",
"... | null | null | null | nielsr | Niels Rogge | 73 | 2025-07-02T17:59:07.000Z | false | ||
2409.09214 | 2024-09-17 | Seed-Music: A Unified Framework for High Quality and Controlled Music Generation | [
"Ye Bai",
"Haonan Chen",
"Jitong Chen",
"Zhuo Chen",
"Yi Deng",
"Xiaohong Dong",
"Lamtharn Hantrakul",
"Weituo Hao",
"Qingqing Huang",
"Zhongyi Huang",
"Dongya Jia",
"Feihu La",
"Duc Le",
"Bochen Li",
"Chumin Li",
"Hui Li",
"Xingxing Li",
"Shouda Liu",
"Wei-Tsung Lu",
"Yiqing L... | null | null | 54 | 4 | 55 | 2024-09-17 | 23 | 34 | 41 | 43 | 1 | 43 | true | 2024-W38 | 2024-09 | false | 1 | 15 | 7 | 70 | 27 | 254 | We introduce Seed-Music, a suite of music generation systems capable of
producing high-quality music with fine-grained style control. Our unified
framework leverages both auto-regressive language modeling and diffusion
approaches to support two key music creation workflows: controlled
music generation and post-producti... | [
{
"name": "Ye Bai",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Haonan Chen",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
"hidden": false
},
{
"name": "Jitong Chen",
"user": null,
... | null | null | null | akhaliq | AK | null | 2024-09-13T22:06:18.000Z | true | ||
2604.15284 | 2026-04-17 | GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens | [
"Roni Itkin",
"Noam Issachar",
"Yehonatan Keypur",
"Yehonatan Keypur",
"Anpei Chen",
"Sagie Benaim"
] | https://github.com/R-Itk/globalsplat | https://r-itk.github.io/globalsplat/ | 24 | 3 | 25 | 2026-04-17 | 15 | 18 | 22 | 24 | 1 | 24 | true | 2026-W16 | 2026-04 | false | 5 | 29 | 38 | 177 | 183 | 707 | The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representation compactness, reconstruction speed, and rendering fidelity. Previous solutions, whether based on iterative optimization or feed-forward inference, suffer from signi... | [
{
"name": "Roni Itkin",
"user": "Roni-It",
"fullname": "Roni Itkin",
"avatar": "/avatars/8b32d51b0adb6a880e84ea3c7c22d743.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Noam Issachar",
"user": "NoamIssachar",
"fullname": "Noam Issachar",
"avatar": "/ava... | HUJI-IL | The Hebrew University of Jerusalem | https://www.gravatar.com/avatar/fbf7c0844f4246fadde2c5ef9867ccaf?d=retro&size=100 | NoamIssachar | Noam Issachar | /avatars/b07432f31d9c29785ac46a3cc0375fc5.svg | 47 | 2026-04-16T00:00:00.000Z | true | |
2510.09259 | 2025-10-15 | Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models | [
"Yongding Tao",
"Tian Wang",
"Yihong Dong",
"Huanyu Liu",
"Kechi Zhang",
"Xiaolong Hu",
"Ge Li"
] | https://github.com/yongding-tao/RL-Data-Contamination | null | 3 | 2 | 4 | 2025-10-15 | 2 | 2 | 2 | 2 | 1 | 2 | true | 2025-W42 | 2025-10 | false | 36 | 47 | 193 | 244 | 756 | 945 | Data contamination poses a significant threat to the reliable evaluation of
Large Language Models (LLMs). This issue arises when benchmark samples may
inadvertently appear in training sets, compromising the validity of reported
performance. While detection methods have been developed for the pre-training
and Supervised... | [
{
"name": "Yongding Tao",
"user": "YongdingTao",
"fullname": "Yongding Tao",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/664b3aebfe822b08e62357f0/keEfUHXnkfwZ4o7588VdC.jpeg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Tian Wang",
"user": n... | PekingU | Peking University | https://www.gravatar.com/avatar/a2cf4e4900d33c5e795f772e8327843b?d=retro&size=100 | YongdingTao | Yongding Tao | 15 | 2025-10-10T10:58:50.000Z | true | ||
2403.02460 | 2024-03-06 | MagicClay: Sculpting Meshes With Generative Neural Fields | [
"Amir Barda",
"Vladimir G. Kim",
"Noam Aigerman",
"Amit H. Bermano",
"Thibault Groueix"
] | https://github.com/amirbarda/MagicClay | null | 7 | 1 | 8 | 2024-03-12 | null | null | null | 6 | 1 | 6 | true | 2024-W10 | 2024-03 | false | 11 | 13 | 41 | 48 | 190 | 218 | The recent developments in neural fields have brought phenomenal capabilities
to the field of shape generation, but they lack crucial properties, such as
incremental control - a fundamental requirement for artistic work. Triangular
meshes, on the other hand, are the representation of choice for most geometry
related ta... | [
{
"name": "Amir Barda",
"user": "Amir001",
"fullname": "Amir Barda",
"avatar": "/avatars/095dfd84599c74d7600228d8104faac9.svg",
"status": "admin_assigned",
"hidden": false
},
{
"name": "Vladimir G. Kim",
"user": null,
"fullname": null,
"avatar": null,
"status": null,
... | null | null | null | akhaliq | AK | 60 | 2024-03-04T20:20:14.000Z | false | ||
2503.17982 | 2025-03-26 | Co-SemDepth: Fast Joint Semantic Segmentation and Depth Estimation on Aerial Images | [
"Yara AlaaEldin",
"Francesca Odone"
] | https://github.com/malga-vision/co-semdepth | null | 0 | 2 | 0 | 2025-03-26 | 0 | 0 | 0 | 0 | 0 | 0 | true | 2025-W13 | 2025-03 | false | 34 | 34 | 141 | 144 | 607 | 611 | Understanding the geometric and semantic properties of the scene is crucial
in autonomous navigation and particularly challenging in the case of Unmanned
Aerial Vehicle (UAV) navigation. Such information may be by obtained by
estimating depth and semantic segmentation maps of the surrounding environment
and for their p... | [
{
"name": "Yara AlaaEldin",
"user": "yaraalaa0",
"fullname": "Yara AlaaEldin",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/Rxkp1GnjCf-u5AlE1-4gi.png",
"status": "extracted_confirmed",
"hidden": false
},
{
"name": "Francesca Odone",
"user": null,
... | null | null | null | yaraalaa0 | Yara AlaaEldin | 11 | 2025-03-23T08:25:07.000Z | true | ||
2601.20524 | 2026-04-10 | AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors | [
"Matic Fučka",
"Vitjan Zavrtanik",
"Danijel Skočaj"
] | https://github.com/MaticFuc/AnomalyVFM | https://maticfuc.github.io/anomaly_vfm/ | 4 | 2 | 7 | 2026-04-10 | 2 | 2 | 4 | 6 | 3 | 6 | true | 2026-W15 | 2026-04 | false | 34 | 42 | 138 | 155 | 462 | 707 | Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent approaches leverage vision-language models (VLMs), such as CLIP, to transfer high-level concept knowledge, methods based on purely vision foundation models (VFMs), like DIN... | [
{
"name": "Matic Fučka",
"user": "MaticFuc",
"fullname": "Matic Fučka",
"avatar": "/avatars/cebc02551b7f0418f5d33466959e0796.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Vitjan Zavrtanik",
"user": null,
"fullname": null,
"avatar": null,
"status": ... | vicoslab | Visual Cognitive Systems Laboratory | MaticFuc | Matic Fučka | /avatars/cebc02551b7f0418f5d33466959e0796.svg | 74 | 2026-04-09T00:00:00.000Z | true | ||
2505.24523 | 2025-06-03 | Stress-testing Machine Generated Text Detection: Shifting Language Models Writing Style to Fool Detectors | [
"Andrea Pedrotti",
"Michele Papucci",
"Cristiano Ciaccio",
"Alessio Miaschi",
"Giovanni Puccetti",
"Felice Dell'Orletta",
"Andrea Esuli"
] | https://github.com/gpucce/control_mgt | null | 9 | 4 | 10 | 2025-06-03 | 8 | 8 | 8 | 8 | 1 | 8 | true | 2025-W23 | 2025-06 | false | 25 | 62 | 121 | 250 | 348 | 679 | Recent advancements in Generative AI and Large Language Models (LLMs) have
enabled the creation of highly realistic synthetic content, raising concerns
about the potential for malicious use, such as misinformation and manipulation.
Moreover, detecting Machine-Generated Text (MGT) remains challenging due to the
lack of ... | [
{
"name": "Andrea Pedrotti",
"user": "andreapdr",
"fullname": "Andrea Pedrotti",
"avatar": "https://cdn-avatars.huggingface.co/v1/production/uploads/616a9f40ebe369e3e0209c00/lBzeeugOSWz-VkhGMr25Z.png",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Michele Papucci",
... | null | null | null | alemiaschi | Alessio Miaschi | 7 | 2025-05-30T12:33:30.000Z | true | ||
2506.09993 | 2025-06-13 | Text-Aware Image Restoration with Diffusion Models | [
"Jaewon Min",
"Jin Hyeon Kim",
"Paul Hyunbin Cho",
"Jaeeun Lee",
"Jihye Park",
"Minkyu Park",
"Sangpil Kim",
"Hyunhee Park",
"Seungryong Kim"
] | https://github.com/cvlab-kaist/TAIR | https://cvlab-kaist.github.io/TAIR/ | 45 | 2 | 45 | 2025-06-13 | 32 | 34 | 37 | 37 | 1 | 37 | true | 2025-W24 | 2025-06 | false | 4 | 41 | 17 | 162 | 77 | 679 | Image restoration aims to recover degraded images. However, existing
diffusion-based restoration methods, despite great success in natural image
restoration, often struggle to faithfully reconstruct textual regions in
degraded images. Those methods frequently generate plausible but incorrect
text-like patterns, a pheno... | [
{
"name": "Jaewon Min",
"user": "Min-Jaewon",
"fullname": "Jaewon Min",
"avatar": "/avatars/b07240cb86315b9e33d14677e02e4024.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Jin Hyeon Kim",
"user": "jinlovespho",
"fullname": "Jin Hyeon Kim",
"avatar": "/a... | null | null | null | Min-Jaewon | Jaewon Min | /avatars/b07240cb86315b9e33d14677e02e4024.svg | 255 | 2025-06-11T17:59:46.000Z | true | |
2406.01574 | 2024-06-04 | MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark | [
"Yubo Wang",
"Xueguang Ma",
"Ge Zhang",
"Yuansheng Ni",
"Abhranil Chandra",
"Shiguang Guo",
"Weiming Ren",
"Aaran Arulraj",
"Xuan He",
"Ziyan Jiang",
"Tianle Li",
"Max Ku",
"Kai Wang",
"Alex Zhuang",
"Rongqi Fan",
"Xiang Yue",
"Wenhu Chen"
] | https://github.com/tiger-ai-lab/mmlu-pro | null | 56 | 3 | 57 | 2024-06-04 | 28 | 31 | 31 | 35 | 2 | 35 | true | 2024-W23 | 2024-06 | false | 1 | 6 | 3 | 41 | 37 | 346 | In the age of large-scale language models, benchmarks like the Massive
Multitask Language Understanding (MMLU) have been pivotal in pushing the
boundaries of what AI can achieve in language comprehension and reasoning
across diverse domains. However, as models continue to improve, their
performance on these benchmarks ... | [
{
"name": "Yubo Wang",
"user": "ubowang",
"fullname": "Yubo Wang",
"avatar": "/avatars/d9c5cf3491243d1f2b1c5df1873ee8e7.svg",
"status": "claimed_verified",
"hidden": false
},
{
"name": "Xueguang Ma",
"user": "MrLight",
"fullname": "Xueguang Ma",
"avatar": "/avatars/45b58d... | null | null | null | akhaliq | AK | 428 | 2024-06-03T17:53:00.000Z | false |
End of preview. Expand in Data Studio
Paper Pulse data
The day-by-day upvote history of every Hugging Face Daily Papers entry since 2024-03-12, updated every day. It powers Paper Pulse (Space).
Built from the past revisions of hysts-bot-data/daily-papers-stats and the paper list in hysts-bot-data/daily-papers, both by @hysts, plus paper details from the public Daily Papers API. Thanks to hysts for keeping that record and for releasing it under CC0 1.0.
Files
| File | Rows | What it holds |
|---|---|---|
series.parquet |
one per paper per day | id (arXiv id), day, upvotes, comments: the count shown on the paper's page that day (last snapshot of the day, UTC) |
papers.parquet |
one per paper | title, Daily Papers date, authors (with Hugging Face accounts when linked), organization, submitter, GitHub repo and stars, abstract (summary), upvotes on day 0/1/3/7, up_close (7 days after the Daily Papers date), peak, purged, and rank within its day, ISO week and month |
purges.parquet |
one per event | days when the Hub removed votes from many papers at once: papers affected (n_drop), votes removed, and whether it was deep |
hourly.parquet |
one per paper per hour | id, ts (UTC), upvotes for the papers featured in the last 10 days, from the hourly snapshots of daily-papers-stats |
age_stats.json |
how papers usually do by age: the distribution of upvotes at the end of day 0..7 after their Daily Papers date, and what papers with a given count at day k ended their first week with (ratios by count bin) | |
meta.json |
last day, number of papers, purge days |
Notes
- Upvotes can go down. People unvote, and on a few days the Hub removed votes from many papers at once (2025-09-12, 2025-12-23, 2026-09-16, 2026-09-18; the cause was not announced). The series keeps the raw value of each day and never corrects it. A day counts as a purge when at least max(250, 2% of papers) dropped.
- Rankings use
up_close, the upvotes 7 days after the Daily Papers date, so a later purge does not rewrite past rankings. Papers younger than 7 days are ranked by their current count, and so are the papers whose Daily Papers date is before the history starts (March 12, 2024), which are flagged withearly. - The source has two collection gaps (13 and 7 days). Days without a snapshot have no row.
- Only papers that were featured on Daily Papers are included (about 18,500), not every paper on the Hub.
License
The series, rankings and purge records are released under CC BY 4.0. The source datasets by @hysts are CC0 1.0. Paper titles and abstracts (title, summary) belong to their authors and are included only to identify each paper; they are not covered by this dataset's license.
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