2 citations · 4 across the 8 of their papers we have counts for
9 papers
Learning from Self-Generated Responses: Reliability--Uncertainty Self-Distillation for Reasoning
Jinhao Pan, Bowen Wei, Yuqing Zhou +1
Reference solutions and question-specific rubrics are not always available to guide the teacher in self-distillation. A large language model's own solution attempts offer an altern…
Confidence-Orchestrated Self-Evolution against Uncertain LLM Feedback
Bowen Wei, Nan Wang, Yuqing Zhou +2
Self-evolving large language models (LLMs) learn by generating their own training tasks and solutions, reducing reliance on human-curated supervision. However, in many reasoning do…
A Logical-Rule Autoencoder for Interpretable Recommendations
Jinhao Pan, Bowen Wei, Ziwei Zhu
Most deep learning recommendation models operate as black boxes, relying on latent representations that obscure their decision process. This lack of intrinsic interpretability rais…
ClawSafety: "Safe" LLMs, Unsafe Agents
Bowen Wei, Yunbei Zhang, Jinhao Pan +5
Personal AI agents like OpenClaw run with elevated privileges on users' local machines, where a single successful prompt injection can leak credentials, redirect financial transact…
Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement
Jinhao Pan, Chahat Raj, Anjishnu Mukherjee +4
Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing methods adopt a suppressive paradigm…
CORTEX: Collaborative LLM Agents for High-Stakes Alert Triage
Bowen Wei, Yuan Shen Tay, Howard Liu +4
Security Operations Centers (SOCs) are overwhelmed by tens of thousands of daily alerts, with only a small fraction corresponding to genuine attacks. This overload creates alert fa…
Bias Association Discovery Framework for Open-Ended LLM Generations
Jinhao Pan, Chahat Raj, Ziwei Zhu
Social biases embedded in Large Language Models (LLMs) raise critical concerns, resulting in representational harms -- unfair or distorted portrayals of demographic groups -- that…
What's Not Said Still Hurts: A Description-Based Evaluation Framework for Measuring Social Bias in LLMs
Jinhao Pan, Chahat Raj, Ziyu Yao +1
Large Language Models (LLMs) often exhibit social biases inherited from their training data. While existing benchmarks evaluate bias by term-based mode through direct term associat…
Countering Mainstream Bias via End-to-End Adaptive Local Learning
Jinhao Pan, Ziwei Zhu, Jianling Wang +2
Collaborative filtering (CF) based recommendations suffer from mainstream bias -- where mainstream users are favored over niche users, leading to poor recommendation quality for ma…