2 citations · 3 across the 11 of their papers we have counts for
6 papers · 1 filter
Task-Differentiated Atomic Skill Expansion and Routing for Continual Learning Across Highly Heterogeneous Tasks
Jiacheng Wang, Xinjia He, Qi Ding +5
Continual learning (CL) is commonly studied under the assumption that sequential tasks are semantically related or structurally similar. However, in highly heterogeneous settings,…
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…
PsychAgent: An Experience-Driven Lifelong Learning Agent for Self-Evolving Psychological Counselor
Yutao Yang, Junsong Li, Qianjun Pan +7
Existing methods for AI psychological counselors predominantly rely on supervised fine-tuning using static dialogue datasets. However, this contrasts with human experts, who contin…
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…
PsychEval: A Multi-Session and Multi-Therapy Benchmark for High-Realism AI Psychological Counselor
Qianjun Pan, Junyi Wang, Jie Zhou +10
To develop a reliable AI for psychological assessment, we introduce \texttt{PsychEval}, a multi-session, multi-therapy, and highly realistic benchmark designed to address three key…