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272986675 | 2409.19679 | 2024-09-29 | SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather Removal | Adverse weather removal aims to restore clear vision under adverse weather conditions. Existing methods are mostly tailored for specific weather types and rely heavily on extensive labeled data. In dealing with these two limitations, this paper presents a pioneering semi-supervised all-in-one adverse weather removal fr... | [
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272986681 | 2409.19554 | 2024-09-29 | Tri-Cam: Practical Eye Gaze Tracking via Camera Network | As human eyes serve as conduits of rich information, unveiling emotions, intentions, and even aspects of an individual's health and overall well-being, gaze tracking also enables various human-computer interaction applications, as well as insights in psychological and medical research. However, existing gaze tracking s... | [
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272986830 | 2409.19672 | 2024-09-29 | Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding | Modeling and leveraging layout reading order in visually-rich documents (VrDs) is critical in document intelligence as it captures the rich structure semantics within documents. Previous works typically formulated layout reading order as a permutation of layout elements, i.e. a sequence containing all the layout elemen... | [
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272987498 | 2409.19546 | 2024-09-29 | Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise | Stochastic approximation is a powerful class of algorithms with celebrated success. However, a large body of previous analysis focuses on stochastic approximations driven by contractive operators, which is not applicable in some important reinforcement learning settings like the average reward setting. This work instea... | [
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272986858 | 2409.19533 | 2024-09-29 | Mixed Chain-of-Psychotherapies for Emotional Support Chatbot | In the realm of mental health support chatbots, it is vital to show empathy and encourage self-exploration to provide tailored solutions. However, current approaches tend to provide general insights or solutions without fully understanding the help-seeker's situation. Therefore, we propose PsyMix, a chatbot that integr... | [
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272986671 | 2409.19676 | 2024-09-29 | See Detail Say Clear: Towards Brain CT Report Generation via Pathological Clue-driven Representation Learning | Brain CT report generation is significant to aid physicians in diagnosing cranial diseases. Recent studies concentrate on handling the consistency between visual and textual pathological features to improve the coherence of report. However, there exist some challenges: 1) Redundant visual representing: Massive irreleva... | [
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272987862 | 2409.19820 | 2024-09-29 | Qompose: A Technique to Select Optimal Algorithm- Specific Layout for Neutral Atom Quantum Architectures | As quantum computing architecture matures, it is important to investigate new technologies that lend unique advantages. In this work, we propose, Qompose, a neutral atom quantum computing framework for efficiently composing quantum circuits on 2-D topologies of neutral atoms. Qompose selects an efficient topology for a... | [
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272987391 | 2409.19629 | 2024-09-29 | A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends | Remaining Useful Life (RUL) prediction is a critical aspect of Prognostics and Health Management (PHM), aimed at predicting the future state of a system to enable timely maintenance and prevent unexpected failures. While existing deep learning methods have shown promise, they often struggle to fully leverage the spatia... | [
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272987801 | 2409.19750 | 2024-09-29 | AstroMLab 2: AstroLLaMA-2-70B Model and Benchmarking Specialised LLMs for Astronomy | Continual pretraining of large language models on domain-specific data has been proposed to enhance performance on downstream tasks. In astronomy, the previous absence of astronomy-focused benchmarks has hindered objective evaluation of these specialized LLM models. Leveraging a recent initiative to curate high-quality... | [
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257681765 | 2409.19587 | 2024-09-29 | Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training | Histopathology whole slide images (WSIs) are being widely used to develop deep learning-based diagnostic solutions, especially for precision oncology. Most of these diagnostic softwares are vulnerable to biases and impurities in the training and test data which can lead to inaccurate diagnoses. For instance, WSIs conta... | [
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272987279 | 2409.19688 | 2024-09-29 | Machine Learning for Raman Spectroscopy-based Cyber-Marine Fish Biochemical Composition Analysis | The rapid and accurate detection of biochemical compositions in fish is a crucial real-world task that facilitates optimal utilization and extraction of high-value products in the seafood industry. Raman spectroscopy provides a promising solution for quickly and non-destructively analyzing the biochemical composition o... | [
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272986853 | 2409.19766 | 2024-09-29 | Towards Robust Extractive Question Answering Models: Rethinking the Training Methodology | This paper proposes a novel training method to improve the robustness of Extractive Question Answering (EQA) models. Previous research has shown that existing models, when trained on EQA datasets that include unanswerable questions, demonstrate a significant lack of robustness against distribution shifts and adversaria... | [
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272986800 | 2409.19660 | 2024-09-29 | All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path Aggregation | Image coding for multi-task applications, catering to both human perception and machine vision, has been extensively investigated. Existing methods often rely on multiple task-specific encoder-decoder pairs, leading to high overhead of parameter and bitrate usage, or face challenges in multi-objective optimization unde... | [
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273404262 | 2410.12799 | 2024-09-29 | Ads Supply Personalization via Doubly Robust Learning | Ads supply personalization aims to balance the revenue and user engagement, two long-term objectives in social media ads, by tailoring the ad quantity and density. In the industry-scale system, the challenge for ads supply lies in modeling the counterfactual effects of a conservative supply treatment (e.g., a small den... | [
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272987296 | 2409.19821 | 2024-09-29 | Tracking Everything in Robotic-Assisted Surgery | Accurate tracking of tissues and instruments in videos is crucial for Robotic-Assisted Minimally Invasive Surgery (RAMIS), as it enables the robot to comprehend the surgical scene with precise locations and interactions of tissues and tools. Traditional keypoint-based sparse tracking is limited by featured points, whil... | [
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272988085 | 2409.19811 | 2024-09-29 | Robust Incremental Structure-from-Motion with Hybrid Features | Structure-from-Motion (SfM) has become a ubiquitous tool for camera calibration and scene reconstruction with many downstream applications in computer vision and beyond. While the state-of-the-art SfM pipelines have reached a high level of maturity in well-textured and well-configured scenes over the last decades, they... | [
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272987528 | 2409.19606 | 2024-09-29 | Hyper-Connections | We present hyper-connections, a simple yet effective method that can serve as an alternative to residual connections. This approach specifically addresses common drawbacks observed in residual connection variants, such as the seesaw effect between gradient vanishing and representation collapse. Theoretically, hyper-con... | [
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272988122 | 2409.19800 | 2024-09-29 | Differentially Private Bilevel Optimization | We present differentially private (DP) algorithms for bilevel optimization, a problem class that received significant attention lately in various machine learning applications. These are the first algorithms for such problems under standard DP constraints, and are also the first to avoid Hessian computations which are ... | [
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272986969 | 2409.19691 | 2024-09-29 | CERD: A Comprehensive Chinese Rhetoric Dataset for Rhetorical Understanding and Generation in Essays | Existing rhetorical understanding and generation datasets or corpora primarily focus on single coarse-grained categories or fine-grained categories, neglecting the common interrelations between different rhetorical devices by treating them as independent sub-tasks. In this paper, we propose the Chinese Essay Rhetoric D... | [
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272987723 | 2409.19831 | 2024-09-30 | Enabling Multi-Robot Collaboration from Single-Human Guidance | Learning collaborative behaviors is essential for multi-agent systems. Traditionally, multi-agent reinforcement learning solves this implicitly through a joint reward and centralized observations, assuming collaborative behavior will emerge. Other studies propose to learn from demonstrations of a group of collaborative... | [
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272987565 | 2409.20329 | 2024-09-30 | Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients | Federated learning (FL) is an appealing paradigm that allows a group of machines (a.k.a. clients) to learn collectively while keeping their data local. However, due to the heterogeneity between the clients' data distributions, the model obtained through the use of FL algorithms may perform poorly on some client's data.... | [
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272988088 | 2409.19840 | 2024-09-30 | Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection | In our study, we explore methods for detecting unwanted content lurking in visual datasets. We provide a theoretical analysis demonstrating that a model capable of successfully partitioning visual data can be obtained using only textual data. Based on the analysis, we propose Hassle-Free Textual Training (HFTT), a stre... | [
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272987949 | 2409.20016 | 2024-09-30 | Dynamic Policy Fusion for User Alignment Without Re-Interaction | Deep reinforcement learning (RL) policies, although optimal in terms of task rewards, may not align with the personal preferences of human users. To ensure this alignment, a naive solution would be to retrain the agent using a reward function that encodes the user's specific preferences. However, such a reward function... | [
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273022991 | 2410.00173 | 2024-09-30 | GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging | Generative Artificial Intelligence (GenAI) is a field of AI that creates new data samples from existing ones. It utilizing deep learning to overcome the scarcity and regulatory constraints of healthcare data by generating new data points that integrate seamlessly with original datasets. This paper explores the backgrou... | [
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272987164 | 2409.20427 | 2024-09-30 | Sufficient and Necessary Explanations (and What Lies in Between) | As complex machine learning models continue to find applications in high-stakes decision-making scenarios, it is crucial that we can explain and understand their predictions. Post-hoc explanation methods provide useful insights by identifying important features in an input $\mathbf{x}$ with respect to the model output ... | [
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272987389 | 2409.20117 | 2024-09-30 | Masked Autoregressive Model for Weather Forecasting | The growing impact of global climate change amplifies the need for accurate and reliable weather forecasting. Traditional autoregressive approaches, while effective for temporal modeling, suffer from error accumulation in long-term prediction tasks. The lead time embedding method has been suggested to address this issu... | [
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273023103 | 2410.00285 | 2024-09-30 | Performance Evaluation of Deep Learning-based Quadrotor UAV Detection and Tracking Methods | Unmanned Aerial Vehicles (UAVs) are becoming more popular in various sectors, offering many benefits, yet introducing significant challenges to privacy and safety. This paper investigates state-of-the-art solutions for detecting and tracking quadrotor UAVs to address these concerns. Cutting-edge deep learning models, s... | [
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272987213 | 2409.20163 | 2024-09-30 | MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants | LLM-based agents have been widely applied as personal assistants, capable of memorizing information from user messages and responding to personal queries. However, there still lacks an objective and automatic evaluation on their memory capability, largely due to the challenges in constructing reliable questions and ans... | [
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272986786 | 2409.20156 | 2024-09-30 | ASTRA: Accurate and Scalable ANNS-based Training of Extreme Classifiers | `Extreme Classification'' (or XC) is the task of annotating data points (queries) with relevant labels (documents), from an extremely large set of $L$ possible labels, arising in search and recommendations. The most successful deep learning paradigm that has emerged over the last decade or so for XC is to embed the que... | [
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272987431 | 2409.20005 | 2024-09-30 | Model Selection with a Shapelet-based Distance Measure for Multi-source Transfer Learning in Time Series Classification | Transfer learning is a common practice that alleviates the need for extensive data to train neural networks. It is performed by pre-training a model using a source dataset and fine-tuning it for a target task. However, not every source dataset is appropriate for each target dataset, especially for time series. In this ... | [
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273022852 | 2410.00064 | 2024-09-30 | M2Distill: Multi-Modal Distillation for Lifelong Imitation Learning | Lifelong imitation learning for manipulation tasks poses significant challenges due to distribution shifts that occur in incremental learning steps. Existing methods often focus on unsupervised skill discovery to construct an ever-growing skill library or distillation from multiple policies, which can lead to scalabili... | [
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273185866 | 2410.03735 | 2024-09-30 | Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling | Specialist language models (LMs) focus on a specific task or domain on which they often outperform generalist LMs of the same size. However, the specialist data needed to pretrain these models is only available in limited amount for most tasks. In this work, we build specialist models from large generalist training set... | [
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272988134 | 2409.19894 | 2024-09-30 | Semantic Alignment-Enhanced Code Translation via an LLM-Based Multi-Agent System | Code translation converts code from one programming language to another while maintaining its original functionality, which is crucial for software migration, system refactoring, and cross-platform development. Traditional rule-based methods rely on manually-written rules, which can be time-consuming and often result i... | [
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272986798 | 2409.19871 | 2024-09-30 | TSI: A Multi-View Representation Learning Approach for Time Series Forecasting | As the growing demand for long sequence time-series forecasting in real-world applications, such as electricity consumption planning, the significance of time series forecasting becomes increasingly crucial across various domains. This is highlighted by recent advancements in representation learning within the field. T... | [
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273022823 | 2410.00242 | 2024-09-30 | Quantized and Asynchronous Federated Learning | Recent advances in federated learning have shown that asynchronous variants can be faster and more scalable than their synchronous counterparts. However, their design does not include quantization, which is necessary in practice to deal with the communication bottleneck. To bridge this gap, we develop a novel algorithm... | [
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272986991 | 2409.20365 | 2024-09-30 | VideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMs | In the video-language domain, recent works in leveraging zero-shot Large Language Model-based reasoning for video understanding have become competitive challengers to previous end-to-end models. However, long video understanding presents unique challenges due to the complexity of reasoning over extended timespans, even... | [
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272987302 | 2409.19930 | 2024-09-30 | EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth Prediction | Accurate depth estimation in endoscopy is vital for successfully implementing computer vision pipelines for various medical procedures and CAD tools. In this paper, we present the EndoDepth benchmark, an evaluation framework designed to assess the robustness of monocular depth prediction models in endoscopic scenarios.... | [
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272987582 | 2409.20252 | 2024-09-30 | What is the Role of Large Language Models in the Evolution of Astronomy Research? | ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text generation capabilities, making them useful for research tasks such as ideation, li... | [
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272987045 | 2409.20116 | 2024-09-30 | REST-HANDS: Rehabilitation with Egocentric Vision Using Smartglasses for Treatment of Hands after Surviving Stroke | Stroke represents the third cause of death and disability worldwide, and is recognised as a significant global health problem. A major challenge for stroke survivors is persistent hand dysfunction, which severely affects the ability to perform daily activities and the overall quality of life. In order to regain their f... | [
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272988008 | 2409.20013 | 2024-09-30 | Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural network | Recent advances in deep learning-based image reconstruction techniques have led to significant progress in phase retrieval using digital in-line holographic microscopy (DIHM). However, existing deep learning-based phase retrieval methods have technical limitations in generalization performance and three-dimensional (3D... | [
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273022726 | 2410.00082 | 2024-09-30 | Graph Residual Noise Learner Network for Brain Connectivity Graph Prediction | A morphological brain graph depicting a connectional fingerprint is of paramount importance for charting brain dysconnectivity patterns. Such data often has missing observations due to various reasons such as time-consuming and incomplete neuroimage processing pipelines. Thus, predicting a target brain graph from a sou... | [
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272987585 | 2409.20426 | 2024-09-30 | Navigating Threats: A Survey of Physical Adversarial Attacks on LiDAR Perception Systems in Autonomous Vehicles | Autonomous vehicles (AVs) rely heavily on LiDAR (Light Detection and Ranging) systems for accurate perception and navigation, providing high-resolution 3D environmental data that is crucial for object detection and classification. However, LiDAR systems are vulnerable to adversarial attacks, which pose significant chal... | [
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272988006 | 2409.20139 | 2024-09-30 | Characterizing Model Robustness via Natural Input Gradients | Adversarially robust models are locally smooth around each data sample so that small perturbations cannot drastically change model outputs. In modern systems, such smoothness is usually obtained via Adversarial Training, which explicitly enforces models to perform well on perturbed examples. In this work, we show the s... | [
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272987008 | 2409.20398 | 2024-09-30 | AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation | The Area Under the ROC Curve (AUC) is a well-known metric for evaluating instance-level long-tail learning problems. In the past two decades, many AUC optimization methods have been proposed to improve model performance under long-tail distributions. In this paper, we explore AUC optimization methods in the context of ... | [
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272987880 | 2409.20052 | 2024-09-30 | Mitigating Propensity Bias of Large Language Models for Recommender Systems | The rapid development of Large Language Models (LLMs) creates new opportunities for recommender systems, especially by exploiting the side information (e.g., descriptions and analyses of items) generated by these models. However, aligning this side information with collaborative information from historical interactions... | [
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272987972 | 2409.20259 | 2024-09-30 | Learning to Ground Existentially Quantified Goals | Goal instructions for autonomous AI agents cannot assume that objects have unique names. Instead, objects in goals must be referred to by providing suitable descriptions. However, this raises problems in both classical planning and generalized planning. The standard approach to handling existentially quantified goals i... | [
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272988096 | 2409.19952 | 2024-09-30 | Image Copy Detection for Diffusion Models | Images produced by diffusion models are increasingly popular in digital artwork and visual marketing. However, such generated images might replicate content from existing ones and pose the challenge of content originality. Existing Image Copy Detection (ICD) models, though accurate in detecting hand-crafted replicas, o... | [
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