Sample Complexity and Representation Ability of Test-time Scaling Paradigms
arXiv:2506.05295v1 Announce Type: cross Abstract: Test-time scaling paradigms have significantly advanced the capabilities of large language models (LLMs) on complex…
Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity
arXiv:2506.03337v1 Announce Type: cross Abstract: Federated Learning enables collaborative fine-tuning of Large Language Models (LLMs) across decentralized Non-Independent and Identically…
Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints
arXiv:2506.04171v1 Announce Type: cross Abstract: Deep generative models have recently been applied to physical systems governed by partial differential equations…
High Performance Space Debris Tracking in Complex Skylight Backgrounds with a Large-Scale Dataset
arXiv:2506.02614v2 Announce Type: replace-cross Abstract: With the rapid development of space exploration, space debris has attracted more attention due to…
TracLLM: A Generic Framework for Attributing Long Context LLMs
arXiv:2506.04202v1 Announce Type: cross Abstract: Long context large language models (LLMs) are deployed in many real-world applications such as RAG,…
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
arXiv:2506.04195v1 Announce Type: cross Abstract: Geometry optimization of atomic structures is a common and crucial task in computational chemistry and…