6 citations · 6 across the 7 of their papers we have counts for
7 papers
Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation
Jijie Zhang, Zhe Ren, Quan Zhang +1
Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence, severely hindering trustworthy…
EviGraph: Evidence-Guided Autonomous Research Agents
Zhenjiang Ren, Ruiji Li, Xujing Zhang +3
Autonomous research agents can generate hypotheses, execute experiments, and draft manuscripts, yet their outputs often contain unsupported claims and inconsistencies between resea…
Self-Improvements in Modern Agentic Systems: A Survey
Zhe Ren, Yimeng Chen, Dandan Guo +9
Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or…
How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation
Yimeng Chen, Zhe Ren, Firas Laakom +3
Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that attacker-published pages are tra…
GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents
Zhe Ren, Yibo Yang, Yimeng Chen +7
Memory benchmarks for LLM agents largely assume single-user settings, leaving shared assistants for hospitals, workplaces, campuses, and households understudied. In these deploymen…
Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents
Shuo Ren, Can Xie, Pu Jian +3
As scientific research becomes increasingly complex, innovative tools are needed to manage vast data, facilitate interdisciplinary collaboration, and accelerate discovery. Large la…
LR^2Bench: Evaluating Long-chain Reflective Reasoning Capabilities of Large Language Models via Constraint Satisfaction Problems
Jianghao Chen, Zhenlin Wei, Zhenjiang Ren +2
Recent progress in Large Reasoning Models (LRMs) has significantly enhanced the reasoning abilities of Large Language Models (LLMs), empowering them to tackle increasingly complex…