From the 1 of 9 linked papers with an AI index.
9 papers
Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
Lei Bai, Zongsheng Cao, Yang Chen +50
The paper introduces Agents-A1, a 35B mixture-of-experts agent model that attains trillion-parameter-level performance by extending the length of reasoning horizons and integrating…
Anything2Skill: Compiling External Knowledge into Reusable Skills for Agents
Qianjun Pan, Yutao Yang, Junsong Li +5
Retrieval-augmented generation (RAG) enables agents to access external knowledge at inference time, but it primarily retrieves fragmented declarative evidence, leaving agents to re…
Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents
Bo Mao, Jie Zhou, Yutao Yang +5
Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learning agents for long-horizon tas…
MA-ProofBench: A Two-Tiered Evaluation of LLMs for Theorem Proving in Mathematical Analysis
Lushi Pu, Weiming Zhang, Xinheng Xie +6
Large Language Models (LLMs) have made notable progress in automated theorem proving, yet existing formal benchmarks remain limited in both mathematical coverage and difficulty. Mo…
MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery
Shangheng Du, Xiangchao Yan, Jinxin Shi +11
Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE), where sustained self-evolution…
AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
Yutao Yang, Junsong Li, Qianjun Pan +9
In practical LLM applications, users repeatedly express stable preferences and requirements, such as reducing hallucinations, following institutional writing conventions, or avoidi…