| project_id,paper_title,pdf_path,source_url,source_kind,license,license_url,license_evidence_url,sha256,bytes,page_count,redistribution_status |
| 013-2026.iclr.10007159,The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs,task_pool/013-2026.iclr.10007159.pdf,https://openreview.net/pdf?id=rIPeatvPy3,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=rIPeatvPy3,7e3079c1246d0003e12e366d2e5a63ac3502a08f11889962a4af5cff787a33b7,1820584,30,bundled_license_verified |
| 016-2025.emnlp.109,CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 Languages,task_pool/016-2025.emnlp.109.pdf,https://aclanthology.org/2025.emnlp-main.109.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2025.emnlp-main.109/,62304c51c0a9742d8b7489910439b966ce3d12f93b1bad42bcd69b36390eb462,1705266,31,bundled_license_verified |
| 017-2026.acl-long.154,Multi-component Causal Tracing in Large Language Models,task_pool/017-2026.acl-long.154.pdf,https://aclanthology.org/2026.acl-long.154.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2026.acl-long.154/,430be4e1ddb509d5cb0f3b5d081efce1d86f528ff714bc5480b90cd8ad7df7a6,1469425,21,bundled_license_verified |
| 018-2026.iclr.10008090,Compositional-ARC: Assessing Systematic Generalization in Abstract Spatial Reasoning,task_pool/018-2026.iclr.10008090.pdf,https://arxiv.org/pdf/2504.01445,arxiv,CC-BY-SA-4.0,https://creativecommons.org/licenses/by-sa/4.0/,https://arxiv.org/abs/2504.01445,e8b58c0d3c75ee88f3d699e0e60b0ae9981b402951af205c1aa6f2a5ecbc195f,1356048,37,bundled_license_verified |
| 019-2026.iclr.10010470,SinkTrack: Attention Sink based Context Anchoring for Large Language Models,task_pool/019-2026.iclr.10010470.pdf,https://arxiv.org/pdf/2604.10027,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2604.10027,1d43629bb77077d60e484b6b868454be1f317ba031a3ae175d8bb121af9fedb6,1718027,17,bundled_license_verified |
| 026-2026.iclr.10007029,Towards Improved Sentence Representations using Token Graphs,task_pool/026-2026.iclr.10007029.pdf,https://openreview.net/pdf?id=stMX9KBhUI,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=stMX9KBhUI,930d4e814c64377e609e20be2bc70342fa01d0c71be7afb89fbe200a721aa078,828690,29,bundled_license_verified |
| 038-2026.iclr.10010317,Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?,task_pool/038-2026.iclr.10010317.pdf,https://arxiv.org/pdf/2510.01161,arxiv,CC-BY-NC-SA-4.0,https://creativecommons.org/licenses/by-nc-sa/4.0/,https://arxiv.org/abs/2510.01161,e26c460dbae97c3c62a166a43740645632c33a0c1d4eba11ae843e7e68dc6381,1115995,16,bundled_license_verified |
| 040-2025.emnlp.281,APLOT: Robust Reward Modeling via Adaptive Preference Learning with Optimal Transport,task_pool/040-2025.emnlp.281.pdf,https://arxiv.org/pdf/2510.10963,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2510.10963,a9f83010af9cbc3d08ed6b1975d180f30e04ee77bbe3e6c73fb9839ac419b154,711326,15,bundled_license_verified |
| 044-2026.acl-long.704,Hallucination Detection in LLMs with Topological Divergence on Attention Graphs,task_pool/044-2026.acl-long.704.pdf,https://arxiv.org/pdf/2504.10063,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2504.10063,71721f32c08f796234caee166616e5a5cda3fd858e5f4169d3514dc750ae11d2,1549905,22,bundled_license_verified |
| 047-2026.acl-long.1062,Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling,task_pool/047-2026.acl-long.1062.pdf,https://arxiv.org/pdf/2604.08178,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2604.08178,672d08643b23686c17538be81d24c5ffe902f9f7ba194762a06f96e8f8393619,1129144,27,bundled_license_verified |
| 052-2026.acl-long.2151,DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents,task_pool/052-2026.acl-long.2151.pdf,https://aclanthology.org/2026.acl-long.2151.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2026.acl-long.2151/,4aa76850f46d9dac947297e70330b70e4a0726932fcb62cc4f1dacc7e13e3bdf,649673,23,bundled_license_verified |
| 069-2026.iclr.10010430,FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging,task_pool/069-2026.iclr.10010430.pdf,https://arxiv.org/pdf/2602.08024,arxiv,CC-BY-NC-ND-4.0,https://creativecommons.org/licenses/by-nc-nd/4.0/,https://arxiv.org/abs/2602.08024,a5496c4ffb59f8defc0683e9ee0b3f0e3e43b5c1f0a4853202f9feba455a98e8,13500070,30,bundled_license_verified |
| 078-2025.iccv.Zhu_Training-free_Geometric_Image_Editing_on_Diffusion_Models_ICCV_2025,Training-free Geometric Image Editing on Diffusion Models,,https://arxiv.org/abs/2507.23300,arxiv_link_only,downstream_redistribution_not_verified,,https://arxiv.org/abs/2507.23300,,,,link_only_no_downstream_license |
| 083-2026.acl-long.2124,"Mind's Eye: A Benchmark of Visual Abstraction, Transformation and Composition for Multimodal LLMs",task_pool/083-2026.acl-long.2124.pdf,https://aclanthology.org/2026.acl-long.2124.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2026.acl-long.2124/,9e74583c8cabe617da6f47f00f6de4b40edd9b6acd85d2ac0cc98590e189152d,6572280,42,bundled_license_verified |
| 084-2026.acl-long.2059,Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding,task_pool/084-2026.acl-long.2059.pdf,https://arxiv.org/pdf/2503.10183,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2503.10183,13a3d0a065948d3ceb509218c05bc519be75c524796bc2638da82ba2f9414d19,13486798,22,bundled_license_verified |
| 085-2026.iclr.10010335,UniCA: Unified Covariate Adaptation for Time Series Foundation Model,task_pool/085-2026.iclr.10010335.pdf,https://openreview.net/pdf?id=I8q4MZb4OP,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=I8q4MZb4OP,2aed00685519d7104a29341938dbbef880aac925aa4bb65c8a4b7365e264ff7e,1237459,41,bundled_license_verified |
| 090-2026.iclr.10009775,PPE: Positional Preservation Embedding for Token Compression in Multimodal Large Language Models,task_pool/090-2026.iclr.10009775.pdf,https://openreview.net/pdf?id=OV0AoK7QEr,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=OV0AoK7QEr,a6c781ae438a911984d15cf4d07498795be8135e00ca3aeb92b94e35b1f7a932,7958598,21,bundled_license_verified |
| 097-2026.iclr.10011287,From Data Statistics to Feature Geometry: How Correlations Shape Superposition,task_pool/097-2026.iclr.10011287.pdf,https://openreview.net/pdf?id=7akSRQS5Xh,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=7akSRQS5Xh,6142fd668e472322a4567b6ae09221e640a09520d39b3c187be6a0d6f12d62ae,19423805,21,bundled_license_verified |
| 098-2026.iclr.10009097,IDER: IDempotent Experience Replay for Reliable Continual Learning,task_pool/098-2026.iclr.10009097.pdf,https://openreview.net/pdf?id=Vr5f3kRvLD,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=Vr5f3kRvLD,be7f18a457a7485dbf061c5b911187411ce4e68f861d61821b8f36ac05612bfd,5506286,20,bundled_license_verified |
| 099-2026.iclr.10010023,Overcoming Joint Intractability with Lossless Hierarchical Speculative Decoding,task_pool/099-2026.iclr.10010023.pdf,https://arxiv.org/pdf/2601.05724,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2601.05724,910af2b7672c5a277cba1967688438525f3c334605301b1bdffa0441ee04cc17,855438,34,bundled_license_verified |
| 102-2026.iclr.10010728,Learning Explicit Single-Cell Dynamics Using ODE Representations,task_pool/102-2026.iclr.10010728.pdf,https://openreview.net/pdf?id=DzSNH5APPl,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=DzSNH5APPl,48763102389b7ccdbe15db0b323cc1475ffb8a68e6448496a71633cb32f0980c,8481761,27,bundled_license_verified |
| 103-2025.emnlp.280,Text Meets Topology: Rethinking Out-of-distribution Detection in Text-Rich Networks,task_pool/103-2025.emnlp.280.pdf,https://arxiv.org/pdf/2508.17690,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2508.17690,04ba426f83541c36a417b98f43ad81a6b9df6d7e150109771fffe6f3d7883b28,4866429,30,bundled_license_verified |
| 104-2026.iclr.10011413,Mirage or Method? How Model-Task Alignment Induces Divergent RL Conclusions,task_pool/104-2026.iclr.10011413.pdf,https://openreview.net/pdf?id=5wmetrh9cn,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=5wmetrh9cn,ffbb1705093572dbbc5295f7ce04cf221d1073530c7c55e303c4f1bb33536333,943331,25,bundled_license_verified |
| 112-2025.emnlp.1545,Context-aware Biases for Length Extrapolation,task_pool/112-2025.emnlp.1545.pdf,https://arxiv.org/pdf/2503.08067,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2503.08067,8b835cf633330e110361a4f5a06528ac441052c2cbdff9e36c43d23361451bb8,13230291,22,bundled_license_verified |
| 114-2026.acl-long.849,Learning to Select: Query-Aware Adaptive Dimension Selection for Dense Retrieval,task_pool/114-2026.acl-long.849.pdf,https://arxiv.org/pdf/2602.03306,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2602.03306,b73d8faaf41ce490bae556f4496ecdd69fa46ed69ef30bae460c69c3f9b54d8f,605143,11,bundled_license_verified |
| 118-2025.emnlp.1496,A Causal Lens for Evaluating Faithfulness Metrics,task_pool/118-2025.emnlp.1496.pdf,https://arxiv.org/pdf/2502.18848,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2502.18848,81186ccb8efaffc66932dd32c66ec4fb70abc42dd9ed315fd295269f3cf8f3c6,1781899,25,bundled_license_verified |
| 119-2026.acl-long.358,GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models,task_pool/119-2026.acl-long.358.pdf,https://aclanthology.org/2026.acl-long.358.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2026.acl-long.358/,b0031d04af12d9df2358513e085c15828a7f0424daca931a0792fad28bb9c593,2876442,13,bundled_license_verified |
| 121-2026.iclr.10011195,HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games,task_pool/121-2026.iclr.10011195.pdf,https://arxiv.org/pdf/2510.12563,arxiv,CC-BY-NC-SA-4.0,https://creativecommons.org/licenses/by-nc-sa/4.0/,https://arxiv.org/abs/2510.12563,32e7d8e65c08e67faa293441777d21da6072fe3d52455dfeaad0a5b67ae11d6c,1276041,40,bundled_license_verified |
| 124-2025.emnlp.1362,"Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements",task_pool/124-2025.emnlp.1362.pdf,https://arxiv.org/pdf/2502.12459,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2502.12459,df74c81ccf12c4b64676a875fb2f9c7757cac800e14d8f5a58a18de5a50b0949,274169,10,bundled_license_verified |
| 128-2026.acl-long.356,SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks,task_pool/128-2026.acl-long.356.pdf,https://arxiv.org/pdf/2604.08865,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2604.08865,53a7edc562b5f45f5334ab6ffb6a41b9ebe5e32b6cf17aae5bcfb000d39ecd71,6345918,22,bundled_license_verified |
| 132-2026.acl-long.1010,Counteracting the Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing,task_pool/132-2026.acl-long.1010.pdf,https://aclanthology.org/2026.acl-long.1010.pdf,acl_anthology,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://aclanthology.org/2026.acl-long.1010/,fd1b4145b556ee4b100e72f93de82abe19851e4c50a49c289dfde8eb59db259d,8566460,18,bundled_license_verified |
| 134-2026.iclr.10008373,GAVEL: Towards Rule-Based Safety through Activation Monitoring,task_pool/134-2026.iclr.10008373.pdf,https://arxiv.org/pdf/2601.19768,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2601.19768,da4f7941a864db6720529c2957db109157012bb6a198c91e543639148d47ea04,1952308,24,bundled_license_verified |
| 136-2026.iclr.10007474,AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport,task_pool/136-2026.iclr.10007474.pdf,https://openreview.net/pdf?id=nTCF3QNsIN,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=nTCF3QNsIN,80c2109c2d4c3966532e8e373fa7594c1aaa1056538a5fecefa10ae97d3a7a86,4919773,19,bundled_license_verified |
| 138-2026.iclr.10008475,SoFlow: Solution Flow Models for One-Step Generative Modeling,task_pool/138-2026.iclr.10008475.pdf,https://openreview.net/pdf?id=cjb03GNqYw,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=cjb03GNqYw,e23c9f503a3d8ee1f4665d25ef4bf42ed5b7161451b76b93e936768f105944df,8533112,19,bundled_license_verified |
| 144-2025.neurips.26300d2734ce0c6bdac69b4c3187b5a2,ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models,,https://arxiv.org/abs/2510.20084,arxiv_link_only,downstream_redistribution_not_verified,,https://arxiv.org/abs/2510.20084,,,,link_only_no_downstream_license |
| 145-2025.icml.wang25ex,A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments,task_pool/145-2025.icml.wang25ex.pdf,https://raw.githubusercontent.com/mlresearch/v267/main/assets/wang25ex/wang25ex.pdf,pmlr,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://proceedings.mlr.press/v267/wang25ex.html,c379e8e2d301b46370a71216fa6680921692968ccf2bf3cfe3e51bf6d1442138,2018778,30,bundled_license_verified |
| 148-2026.iclr.10008008,Self-Consistency Improves the Trustworthiness of Self-Interpretable GNNs,task_pool/148-2026.iclr.10008008.pdf,https://openreview.net/pdf?id=hxGdAUn3sB,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=hxGdAUn3sB,670b047ee887417e8edb72cf92b448eacec641f247c01b6f5e32d12377623d3f,10445368,25,bundled_license_verified |
| 2025.icml.bashari25a,Robust Conformal Outlier Detection under Contaminated Reference Data,task_pool/2025.icml.bashari25a.pdf,https://raw.githubusercontent.com/mlresearch/v267/main/assets/bashari25a/bashari25a.pdf,pmlr,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://proceedings.mlr.press/v267/bashari25a.html,dfc5fb817f9dd17545dfd1683c1c38fda1570a513d485abb384129a9dbc9e954,1516901,51,bundled_license_verified |
| 2025.icml.chen25be,VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters,task_pool/2025.icml.chen25be.pdf,https://openreview.net/pdf?id=5DSj3MfWrB,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=5DSj3MfWrB,16de0783febf439099a0f85b78c0c91e61ddaf8eb630107e41e3c4d5fcbd796f,2460712,29,bundled_license_verified |
| 2025.icml.deng25d,Predicting mutational effects on protein binding from folding energy,task_pool/2025.icml.deng25d.pdf,https://arxiv.org/pdf/2507.05502,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2507.05502,f40c893310e485d106df81f3f3706f232f10a64f11074f37fa862cab4a26042c,2334764,23,bundled_license_verified |
| 2025.icml.schopmans25a,Temperature-Annealed Boltzmann Generators,task_pool/2025.icml.schopmans25a.pdf,https://arxiv.org/pdf/2501.19077,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2501.19077,4c4c86ce56f85d1c3fc5e8b25efc0f81d55452ad76de63dcb2f70ad544982154,5455422,34,bundled_license_verified |
| 2025.icml.sun25l,FlatQuant: Flatness Matters for LLM Quantization,task_pool/2025.icml.sun25l.pdf,https://arxiv.org/pdf/2410.09426v4,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=uTz2Utym5n,06a3ac8f82c56c55c86b3fe8800bbab08a68058fb088fffc05d78efa03da9a68,11932683,27,bundled_license_verified |
| 2025.neurips.0d5c9d43eb13c98db21eeb92c7c986d8,pLSTM: parallelizable Linear Source Transition Mark networks,task_pool/2025.neurips.0d5c9d43eb13c98db21eeb92c7c986d8.pdf,https://arxiv.org/pdf/2506.11997,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2506.11997,54f7ca2a762fee53f52654c271172aec3cfc2eabb69c4959f95ecb29cfed3c7b,826874,24,bundled_license_verified |
| 2025.neurips.67101f97dc23fcc10346091181fff6cb,RobustMerge: Parameter-Efficient Model Merging for MLLMs with Direction Robustness,,https://arxiv.org/abs/2502.17159,arxiv_link_only,downstream_redistribution_not_verified,,https://arxiv.org/abs/2502.17159,,,,link_only_no_downstream_license |
| 2025.neurips.e323ebf7c91a4ca061612ba4a2f2164d,A Simple Linear Patch Revives Layer-Pruned Large Language Models,,https://arxiv.org/abs/2505.24680,arxiv_link_only,downstream_redistribution_not_verified,,https://arxiv.org/abs/2505.24680,,,,link_only_no_downstream_license |
| 2026.acl-long.2069,Parallel Test-Time Scaling for Latent Reasoning Models,task_pool/2026.acl-long.2069.pdf,https://arxiv.org/pdf/2510.07745,arxiv,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://arxiv.org/abs/2510.07745,74cf224420ff66b56594061e6c7c7caaa1ec8b8b0721a5dafcd2dfb830b23d22,2854013,18,bundled_license_verified |
| 2026.iclr.10011500,VisionTrim: Unified Vision Token Compression for Training-Free MLLM Acceleration,task_pool/2026.iclr.10011500.pdf,https://openreview.net/pdf?id=57IXIg6nZ0,openreview,CC-BY-4.0,https://creativecommons.org/licenses/by/4.0/,https://openreview.net/forum?id=57IXIg6nZ0,69e8a9d7879416ef2831d89e0e57fc9a3664b5ddbc5d364a276a49d7930fde23,7437103,31,bundled_license_verified |
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