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arXiv:2603.00620v1 Announce Type: new Abstract: The growing number of languages considered in multilingual NLP, including new datasets and tasks, poses challenges regarding properly and accurately...
arXiv:2603.00621v1 Announce Type: new Abstract: Research in CDCR remains fragmented due to heterogeneous dataset formats, varying annotation standards, and the predominance of the CDCR definition...
arXiv:2603.00623v1 Announce Type: new Abstract: Agentic systems augment large language models with external tools and iterative decision making, enabling complex tasks such as deep research,...
arXiv:2603.00624v1 Announce Type: new Abstract: Catastrophic forgetting, the tendency of neural networks to forget previously learned knowledge when learning new tasks, has been a major...
arXiv:2603.00628v1 Announce Type: new Abstract: We present an experimental validation framework for space robotics that leverages underwater environments to approximate microgravity dynamics. While neutral buoyancy...
arXiv:2603.00629v1 Announce Type: new Abstract: Large time series models (LTMs) have emerged as powerful tools for universal forecasting, yet they often struggle with the inherent...
arXiv:2603.00631v1 Announce Type: new Abstract: LiTS is a modular Python framework for LLM reasoning via tree search. It decomposes tree search into three reusable components...
arXiv:2603.00632v1 Announce Type: new Abstract: Semantic IDs (SIDs) are compact discrete representations derived from multimodal item features, serving as a unified abstraction for ID-based and...
arXiv:2603.00634v1 Announce Type: new Abstract: Multilingual falsehoods threaten information integrity worldwide, yet detection benchmarks remain confined to English or a few high-resource languages, leaving low-resource...
arXiv:2603.00636v1 Announce Type: new Abstract: We propose a retrodictive forecasting paradigm for time series: instead of predicting the future from the past, we identify the...
arXiv:2603.00638v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly adopted as the backbone of recommender systems. However, user-item interactions in real-world scenarios are...
arXiv:2603.00643v1 Announce Type: new Abstract: This position paper argues that the evaluation of modern visual processing systems should no longer be driven primarily by single-metric...
arXiv:2603.00646v1 Announce Type: new Abstract: Agent-native social platforms such as Moltbook are rapidly emerging, yet they inherit and amplify classical influence and abuse attacks, where...
arXiv:2603.00649v1 Announce Type: new Abstract: Assessing the correctness of patches generated by Automated Program Repair (APR) is a major bottleneck. Manual validation is labor-intensive and...
arXiv:2603.00651v1 Announce Type: new Abstract: Dataset pruning has been widely studied for 2D images to remove redundancy and accelerate training, while particular pruning methods for...
arXiv:2603.00654v1 Announce Type: new Abstract: Collaborative perception (CP) enhances scene understanding through multi-agent information sharing. While LiDAR-centric systems offer precise geometry, high costs and performance...
arXiv:2603.00655v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) widely adopt multi-layer visual feature fusion to enhance visual representation. However, existing approaches typically...
arXiv:2603.00656v1 Announce Type: new Abstract: Real-world user requests to LLM agents are often underspecified. Agents must interact to acquire missing information and make correct downstream...
arXiv:2603.00663v1 Announce Type: new Abstract: The Moving Target Vehicle Routing Problem (MT-VRP) seeks trajectories for several agents that intercept a set of moving targets, subject...
arXiv:2603.00666v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training over distributed private data. However, sustaining open participation requires incentive mechanisms that compensate...
arXiv:2603.00667v1 Announce Type: new Abstract: Computational pathology has advanced rapidly in recent years, driven by domain-specific image encoders and growing interest in using vision-language models...
arXiv:2603.00668v1 Announce Type: new Abstract: Low-field magnetic resonance imaging (MRI) provides affordable access to diagnostic imaging but suffers from prolonged acquisition and limited image quality....
arXiv:2603.00669v1 Announce Type: new Abstract: Sustainability disclosure standards (e.g., GRI, SASB, TCFD, IFRS S2) are comprehensive yet lengthy, terminology-dense, and highly cross-referential, hindering structured analysis...
arXiv:2603.00676v1 Announce Type: new Abstract: Existing mobile device control agents often perform poorly when solving complex tasks requiring long-horizon planning and precise operations, typically due...