14 citations · 24 across the 12 of their papers we have counts for
12 papers
The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents
Xing Zhang, Yanwei Cui, Guanghui Wang +4
A self-evolving agent retires its bad skills by watching them fail, so what happens when the judge cannot see the failures? Skill retirement is the structural constraint that keeps…
Who Grades the Grader? Co-Evolving Evaluation Metrics and Skills for Self-Improving LLM Agents
Xing Zhang, Guanghui Wang, Yanwei Cui +4
Self-evolving agent systems create, revise, and retire their own skills, but every such loop assumes a reliable evaluation metric already exists. In many real applications none doe…
The Alignment Floor: How Persona Customization Breaks Safety in Weakly-Aligned LLMs
Xing Zhang, Guanghui Wang, Yanwei Cui +4
Telling an LLM to "be enthusiastic" raises its sycophancy rate from 30\% to 50\% on a lightly-aligned model, but has zero effect on a strongly-aligned one. We define this gap as th…
Guardrails Beat Guidance: A Large-Scale Study of Rules, Skills, and Persistent Configuration for Coding Agents
Xing Zhang, Guanghui Wang, Yanwei Cui +4
Random rules improve a coding agent's task performance as much as expert-curated ones (both pp on a discriminative subset of SWE-bench Verified), and in our data every indiv…
Prompt Optimization Is a Coin Flip: Diagnosing When It Helps in Compound AI Systems
Xing Zhang, Guanghui Wang, Yanwei Cui +4
Prompt optimization in compound AI systems is statistically indistinguishable from a coin flip: across 72 optimization runs on Claude Haiku 4.5 (6 methods 4 tasks …
Ratchet: How Reliable Must an LLM Judge Be to Retire a Skill?
Xing Zhang, Yanwei Cui, Guanghui Wang +4
A large language model (LLM) agent that writes and edits its own skill library must also decide which skills to keep, from one noisy scalar per skill. The answer is exact: a judge…
Library Drift: Diagnosing and Fixing a Silent Failure Mode in Self-Evolving LLM Skill Libraries
Xing Zhang, Yanwei Cui, Guanghui Wang +4
Self-evolving skill libraries face a silent failure mode we term \emph{library drift}: unbounded skill accumulation without outcome-driven lifecycle management causes retrieval deg…
Hindsight Preference Optimization for Financial Time Series Advisory
Yanwei Cui, Guanghui Wang, Xing Zhang +7
Time series models predict numbers; decision-makers need advisory -- directional signals with reasoning, actionable suggestions, and risk management. Training language models for s…
From Debate to Decision: Conformal Social Choice for Safe Multi-Agent Deliberation
Mengdie Flora Wang, Haochen Xie, Guanghui Wang +9
Multi-agent debate improves LLM reasoning, yet agreement is not evidence of correctness. When agents converge on a wrong answer through social reinforcement, consensus stopping com…
Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents
Xing Zhang, Guanghui Wang, Yanwei Cui +4
As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory systems and agent skill disc…
FinTextQA: A Dataset for Long-form Financial Question Answering
Jian Chen, Peilin Zhou, Yining Hua +5
Accurate evaluation of financial question answering (QA) systems necessitates a comprehensive dataset encompassing diverse question types and contexts. However, current financial Q…
Software Code Quality Measurement: Implications from Metric Distributions
Siyuan Jin, Mianmian Zhang, Yekai Guo +5
Software code quality is a construct with three dimensions: maintainability, reliability, and functionality. Although many firms have incorporated code quality metrics in their ope…