activity
20242026
most citedWhere LLM Agents Fail and How They can Learn From Failures

3 citations · 8 across the 13 of their papers we have counts for

collaborators

11 papers

cs.AI2026

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

Xiaomin Li, Yuexing Hao, Jianheng Hou +90

Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…

cs.AI2026

Modular Cognitive Architecture Emerges in Large Language Models

Pengrui Han, Jacob Andreas, Evelina Fedorenko +1

The human brain exhibits a striking degree of functional specialization, with distinct networks supporting language, formal reasoning, reasoning about other minds, and reasoning ab…

cs.CL2026

Thought-Retriever: Don't Just Retrieve Raw Data, Retrieve Thoughts for Memory-Augmented Agentic Systems

Tao Feng, Pengrui Han, Guanyu Lin +2

Large language models (LLMs) have transformed AI research thanks to their powerful internal capabilities and knowledge. However, existing LLMs still fail to effectively incorporate…

cs.AI2026

Steer2Adapt: Dynamically Composing Steering Vectors Elicits Efficient Adaptation of LLMs

Pengrui Han, Xueqiang Xu, Keyang Xuan +12

Activation steering has emerged as a promising approach for efficiently adapting large language models (LLMs) to downstream behaviors. However, most existing steering methods rely…

cs.AI20263 cited

Large Language Model Reasoning Failures

Peiyang Song, Pengrui Han, Noah Goodman

Large Language Models (LLMs) have exhibited remarkable reasoning capabilities, achieving impressive results across a wide range of tasks. Despite these advances, significant reason…

cs.CL2026

Rethinking the Reranker: Boundary-Aware Evidence Selection for Robust Retrieval-Augmented Generation

Jiashuo Sun, Pengcheng Jiang, Saizhuo Wang +13

Retrieval-Augmented Generation (RAG) systems remain brittle under realistic retrieval noise, even when the required evidence appears in the top-K results. A key reason is that retr…