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전체 전문분석자료
arXiv:2603.03511v1 Announce Type: new Abstract: We aim to learn wavefunctions simulated by time-dependent density functional theory (TDDFT), which can be efficiently represented as linear combination …
arXiv:2603.03523v1 Announce Type: new Abstract: We study reinforcement learning in infinite-horizon discounted Markov decision processes with continuous state spaces, where data are generated online from …
arXiv:2603.03524v1 Announce Type: new Abstract: As strong general reasoners, large language models (LLMs) encounter diverse domains and tasks, where the ability to adapt and self-improve …
arXiv:2603.03527v1 Announce Type: new Abstract: Vision-Language Models (VLMs) with their multimodal capabilities have demonstrated remarkable success in almost all domains, including education, transportation, healthcare, energy, …
arXiv:2603.03529v1 Announce Type: new Abstract: We introduce mlx-snn, the first spiking neural network (SNN) library built natively on Apple's MLX framework. As SNN research grows …
arXiv:2603.03530v1 Announce Type: new Abstract: Frozen self-supervised representations often transfer well with only a few labels across many semantic tasks. We argue that a single …
arXiv:2603.03531v1 Announce Type: new Abstract: Accurate prediction of terrestrial ecosystem carbon fluxes (e.g., CO$_2$, GPP, and CH$_4$) is essential for understanding the global carbon cycle …
arXiv:2603.03535v1 Announce Type: new Abstract: While large language models (LLMs) fine-tuned with lightweight adapters achieve strong performance across diverse tasks, their performance on individual tasks …
arXiv:2603.03538v1 Announce Type: new Abstract: Large language models with chain-of-thought generation have demonstrated great potential for producing complex mathematical proofs. However, their reasoning can often …
arXiv:2603.03578v1 Announce Type: new Abstract: Optimal transport (OT) finds a least cost transport plan between two probability distributions using a cost matrix defined on pairs …
arXiv:2603.03595v1 Announce Type: new Abstract: Coordinating multiple autonomous agents to explore and serve spatially heterogeneous demand requires jointly learning unknown spatial patterns and planning trajectories …
arXiv:2603.03597v1 Announce Type: new Abstract: The rapid progress of large language models (LLMs) is increasingly constrained by memory and deployment costs, motivating compression methods for …