15 citations · 21 across the 11 of their papers we have counts for
13 papers
The Trust Paradox in LLM-Based Multi-Agent Systems: When Collaboration Becomes a Security Vulnerability
Zijie Xu, Minfeng Qi, Shiqing Wu +4
Multi-agent systems powered by large language models are advancing rapidly, yet the tension between mutual trust and security remains underexplored. We introduce and empirically va…
Faithful, Unfaithful or Ambiguous? Multi-Agent Debate with Initial Stance for Summary Evaluation
Mahnaz Koupaee, Jake W. Vincent, Saab Mansour +9
Faithfulness evaluators based on large language models (LLMs) are often fooled by the fluency of the text and struggle with identifying errors in the summaries. We propose an appro…
Stealthy Jailbreak Attacks on Large Language Models via Benign Data Mirroring
Honglin Mu, Han He, Yuxin Zhou +9
Large language model (LLM) safety is a critical issue, with numerous studies employing red team testing to enhance model security. Among these, jailbreak methods explore potential…
CriSPO: Multi-Aspect Critique-Suggestion-guided Automatic Prompt Optimization for Text Generation
Han He, Qianchu Liu, Lei Xu +4
Existing automatic prompt engineering methods are typically designed for discriminative tasks, where new task prompts are iteratively refined with limited feedback from a single me…
Unleashing the True Potential of Sequence-to-Sequence Models for Sequence Tagging and Structure Parsing
Han He, Jinho D. Choi
Sequence-to-Sequence (S2S) models have achieved remarkable success on various text generation tasks. However, learning complex structures with S2S models remains challenging as ext…
DFEE: Interactive DataFlow Execution and Evaluation Kit
Han He, Song Feng, Daniele Bonadiman +2
DataFlow has been emerging as a new paradigm for building task-oriented chatbots due to its expressive semantic representations of the dialogue tasks. Despite the availability of a…