Quality follows upgrading
Academic
arXiv:2603.20578v1 Announce Type: new Abstract: The prevailing approach to improving large language model (LLM) reasoning has centered on expanding context windows, implicitly assuming that more …
arXiv:2603.20246v1 Announce Type: new Abstract: Speech brain--computer interfaces require decoders that translate intracortical activity into linguistic output while remaining robust to limited data and day-to-day …
arXiv:2603.20425v1 Announce Type: new Abstract: Food security policy formulation in data-scarce regions remains a critical challenge due to limited structured datasets, fragmented textual reports, and …
arXiv:2603.20218v1 Announce Type: new Abstract: Retrieval-augmented generation improves large language models' accuracy by adding relevant retrieved text to the prompt. Chunk level caching (CLC) accelerates …
arXiv:2603.21140v1 Announce Type: new Abstract: Training large language models (LLMs) with synthetic reasoning data has become a popular approach to enhancing their reasoning capabilities, while …
arXiv:2603.20662v1 Announce Type: new Abstract: Despite remarkable advances in large Vision-Language Models (VLMs), spatial reasoning remains a persistent challenge. In this work, we investigate how …
arXiv:2603.20285v1 Announce Type: new Abstract: Cooperative multi-agent methods for embodied AI are almost universally evaluated under idealized communication: zero latency, no packet loss, and unlimited …
arXiv:2603.20212v1 Announce Type: new Abstract: Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Reward …
arXiv:2603.20633v1 Announce Type: new Abstract: We present Seed1.8, a foundation model aimed at generalized real-world agency: going beyond single-turn prediction to multi-turn interaction, tool use, …
arXiv:2603.20986v1 Announce Type: new Abstract: Multiphysics simulation frameworks such as MOOSE provide rigorous engines for phase-field materials modeling, yet adoption is constrained by the expertise …
arXiv:2603.20925v1 Announce Type: new Abstract: As agentic systems move into real-world deployments, their decisions increasingly depend on external inputs such as retrieved content, tool outputs, …
arXiv:2603.20270v1 Announce Type: new Abstract: Generating executable simulations from natural language specifications remains a challenging problem due to the limited reasoning capacity of large language …
