提出从清单式评估转向基于稳态聚类的AGI评估新框架，挑战传统多领域能力测试的局限
arXiv:2510.15236v2 Announce Type: replace Abstract: Contemporary AGI evaluations report multidomain capability profiles, yet they typically assign sym…
最新基准Relay-Bench揭示：顶级LLM在多领域推理链上仅得43.3%，尚未饱和
arXiv:2607.18438v1 Announce Type: cross Abstract: Introducing Relay-Bench, an unsaturated, holistic, text-only benchmark that measures LLMs' ability t…
多领域测试时扩展中，如何重新设计奖励模型？新论文提出关键思考。
arXiv:2510.00492v3 Announce Type: replace Abstract: The reliability of large language models (LLMs) during test-time scaling is often assessed with \e…
全新多领域科学代码搜索数据集及基准发布，填补代码检索领域空白
arXiv:2607.05443v1 Announce Type: cross Abstract: Scientists increasingly rely on open-source tools to support their research workflows, yet discoveri…
跨领域流式视频任务指导新框架，支持实时干预与多场景适应。
arXiv:2607.02991v1 Announce Type: new Abstract: While multimodal Large Language Models (MLLMs) excel at offline video understanding, an interesting qu…
14种自动摘要指标与LLM评估器的大规模元评估，揭示跨领域长文档评估挑战，为反思式总结提供新框架。
arXiv:2604.25665v2 Announce Type: replace-cross Abstract: Reliable evaluation of large language model (LLM)-generated summaries remains an open challe…
用科学数据微调大模型反而更易“信口开河”？最新多领域评估揭示幻觉风险，警示科学应用需谨慎。
arXiv:2606.21359v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet…
首个针对GPT-Image-2生成文本丰富图像的多领域检测基准，应对AI合成内容鉴别挑战
arXiv:2606.19259v1 Announce Type: new Abstract: Text-rich images often contain privacy-sensitive, transactional, or decision-relevant information. As …
大模型Agent在行动中是否隐藏歧视？新基准AgentFairBench可低成本、可复现地评估多领域人口统计偏差。
arXiv:2606.16723v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly take actions (screening applicants, recommending credit…
提出SoCRATES框架，解决LLM调解员在多领域和社会认知变化下的自动评估难题，填补现有测试平台局限。
arXiv:2606.05563v1 Announce Type: new Abstract: Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by…
多领域强化学习中的跨域干扰与恢复难题，这篇论文提出全新局部扰动理论，为RL领域交叉应用提供新思路。
arXiv:2606.02398v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training improves large language models (LLMs) on individual domains …
新框架SkillWeave通过模块化技能包让大模型高效专业化，成本低、兼容多领域
arXiv:2605.22205v1 Announce Type: new Abstract: Large language models increasingly require specialization across diverse domains, yet existing approac…
专为专业领域设计的评估基准，多域知识、高难度问答，考验大模型真实能力
arXiv:2510.18941v2 Announce Type: replace-cross Abstract: Evaluating progress in large language models (LLMs) is often constrained by the challenge of…