4 citations · 13 across the 29 of their papers we have counts for
10 papers · 1 filter
Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents
Wei-Chieh Huang, Weizhi Zhang, Yuchen Wu +12
Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely the underlying medium in which…
RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills
Weizhi Zhang, Zechen Li, Hamid Palangi +16
The LLM-empowered personal health agents with user health (sensor) metrics have offered a promising pathway to alleviate global disparities in healthcare access. However, large-sca…
SciCustom: A Framework for Custom Evaluation of Scientific Capabilities in Large Language Models
Yiyang Gu, Junwei Yang, Junyu Luo +15
Large language models (LLMs) are increasingly applied to scientific research, yet existing evaluations often fail to reflect the fine-grained capabilities required in practice. Mos…
When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang +16
As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as addi…
MemoryCD: Benchmarking Long-Context User Memory of LLM Agents for Lifelong Cross-Domain Personalization
Weizhi Zhang, Xiaokai Wei, Wei-Chieh Huang +4
Recent advancements in Large Language Models (LLMs) have expanded context windows to million-token scales, yet benchmarks for evaluating memory remain limited to short-session synt…
LLM-MemCluster: Empowering Large Language Models with Dynamic Memory for Text Clustering
Yuanjie Zhu, Liangwei Yang, Ke Xu +4
Large Language Models (LLMs) are reshaping unsupervised learning by offering an unprecedented ability to perform text clustering based on their deep semantic understanding. However…
Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs
Yangning Li, Weizhi Zhang, Yuyao Yang +17
Retrieval-Augmented Generation (RAG) lifts the factuality of Large Language Models (LLMs) by injecting external knowledge, yet it falls short on problems that demand multi-step inf…
MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning
Yusheng Zhao, Xiao Luo, Weizhi Zhang +4
The ability to reason is one of the most fundamental capabilities of large language models (LLMs), enabling a wide range of downstream tasks through sophisticated problem-solving.…
LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey
Henry Peng Zou, Wei-Chieh Huang, Yaozu Wu +17
Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-based agents still face significant…
Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Junyu Luo, Weizhi Zhang, Ye Yuan +23
The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic a…