6 papers
ContextWeave: A Real-World Workflow Benchmark
Bo Wang, Yuqian Yao, Enxi Wang +25
Memory is essential as language agents move from isolated tasks to long-horizon, stateful workflows, yet existing evaluations often reduce it to retrieval or question answering. We…
Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents
Yuxuan Cai, Wei Li, Jie Zhou +4
Online lifelong learning agents must decide not only how to act but also when to consult prior experience to continually improve on long-horizon tasks. Existing methods typically r…
WebForge: Breaking the Realism-Reproducibility-Scalability Trilemma in Browser Agent Benchmark
Peng Yuan, Yuyang Yin, Yuxuan Cai +1
Existing browser agent benchmarks face a fundamental trilemma: real-website benchmarks lack reproducibility due to content drift, controlled environments sacrifice realism by omitt…
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…
Building Self-Evolving Agents via Experience-Driven Lifelong Learning: A Framework and Benchmark
Yuxuan Cai, Yipeng Hao, Jie Zhou +14
As AI advances toward general intelligence, the focus is shifting from systems optimized for static tasks to creating open-ended agents that learn continuously. In this paper, we i…
Task-Core Memory Management and Consolidation for Long-term Continual Learning
Tianyu Huai, Jie Zhou, Yuxuan Cai +5
In this paper, we focus on a long-term continual learning (CL) task, where a model learns sequentially from a stream of vast tasks over time, acquiring new knowledge while retainin…