Trends · 研究趋势
数据来自 Hugging Face 论文的 AI 提取关键词,按月统计研究方向的增长与热度。
Jianlyu Chen, Yuyang Hu, Hongjin Qian +8 authors
DisCo is a research agent that distills operational knowledge into reusable skills, significantly improving autonomous ML research performance across benchmarks.
Tianxin Wei, Ting-Wei Li, Zhining Liu +26 authors
Agentic reasoning redefines large language models as autonomous agents capable of planning, acting, and learning through continuous interaction in dynamic environments across single-agent and multi-agent frameworks.
GLM-5 Team, Aohan Zeng, Xin Lv +183 authors
GLM-5 advances foundation models with DSA for cost reduction, asynchronous reinforcement learning for improved alignment, and enhanced coding capabilities for real-world software engineering.
Ming Hu, Chenglong Ma, Wei Li +100 authors
Sci-LLMs are evolving through a co-development with scientific data, addressing unique challenges like multimodal and domain-specific information, and are moving towards autonomous, closed-loop systems in scientific research.
Bowen Ye, Rang Li, Qibin Yang +10 authors
Claw-Eval addresses limitations in agent benchmarks by providing comprehensive evaluation across multiple modalities with trajectory-aware grading and safety assessments.
Yang Xiao, Mohan Jiang, Jie Sun +18 authors
LIMI demonstrates that sophisticated agentic intelligence can emerge from minimal, strategically curated demonstrations, outperforming data-intensive models on agency benchmarks.
Bobo Li, Hao Fei, Tianjie Ju +2 authors
OmniScientist is an end-to-end omni-modal AI scientist that performs multidisciplinary research directly from heterogeneous raw evidence using autonomous agents and lifecycle-wide perception, improving evidence-grounded discovery across diverse scientific modalities.
Nex-AGI Team, Yuxuan Cai, Lu Chen +62 authors
The introduction of NexAU, NexA4A, and NexGAP enables the scaling of complexity, diversity, and fidelity in interactive environments for training large language models as autonomous agents, resulting in superior performance.
Zhenxiong Yu, Zhi Yang, Zhiheng Jin +19 authors
Spider-Sense framework provides intrinsic and selective agent security through event-driven defense with intrinsic risk sensing, achieving low attack success and false positive rates with minimal latency overhead.
Chunqiu Steven Xia, Yinlin Deng, Soren Dunn +1 authors
Agentless, a two-phase approach to software development automation, achieves high performance and low cost compared to complex autonomous agents on the SWE-bench Lite benchmark.
Zhilin Wang, Han Song, Runzhe Zhan +13 authors
Autonomous agents evaluate policy improvement through iterative editing within fixed budgets, revealing that successful policy evolution requires both task-specific mechanisms and feedback-constrained refinement.
Shuyan Zhou, Frank F. Xu, Hao Zhu +8 authors
WebArena, a realistic and reproducible environment, evaluates the performance of autonomous agents performing complex tasks on websites using benchmark tasks that require human-like reasoning.
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