1 citations · 1 across the 9 of their papers we have counts for
11 papers
RADNPO: Reference-free Adaptive Negative Preference Optimization for LLM Unlearning
Shenghan Tan, Ziyi Zhou, Wenpeng Hu +1
Large language models (LLMs) can memorize sensitive, private, or copyrighted content during pre-training, making machine unlearning necessary for removing targeted knowledge. Recen…
Benign Alone, Harmful Together: Exploiting Experience Composition in Self-Evolving LLM Agents
Bingyu Yan, Xiaoming Zhang, Chaozhuo Li +3
Self-evolving large language model agents improve their capabilities by distilling interaction trajectories into persistent experiences. Yet this mechanism introduces a new safety…
Evo-Attacker: Memory-Augmented Reinforcement Learning for Long-Horizon Tool Attacks on LLM-MAS
Bingyu Yan, Xiaoming Zhang, Jinyu Hou +4
While Large Language Model-based Multi-Agent Systems (LLM-MAS) demonstrate remarkable capabilities in solving complex tasks by orchestrating specialized agents and external tools,…
PropGuard: Safeguarding LLM-MAS via Propagation-Aware Exploration and Remediation
Bingyu Yan, Xiaoming Zhang, Jinyu Hou +4
LLM-based multi-agent systems (LLM-MAS) have become a promising paradigm for solving complex tasks through role specialization, tool use, memory, and collaborative reasoning. Howev…
A2Eval: Agentic and Automated Evaluation for Embodied Brain
Shuai Zhang, Jiayu Hu, Zijie Chen +9
Current embodied VLM evaluation relies on static, expert-defined, manually annotated benchmarks that exhibit severe redundancy and coverage imbalance. This labor intensive paradigm…
Attack the Messages, Not the Agents: A Multi-round Adaptive Stealthy Tampering Framework for LLM-MAS
Bingyu Yan, Ziyi Zhou, Xiaoming Zhang +5
Large language model-based multi-agent systems (LLM-MAS) effectively accomplish complex and dynamic tasks through inter-agent communication, but this reliance introduces substantia…
LLMs are Introvert
Litian Zhang, Xiaoming Zhang, Bingyu Yan +5
The exponential growth of social media and generative AI has transformed information dissemination, fostering connectivity but also accelerating the spread of misinformation. Under…
Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection
Ziyi Zhou, Xiaoming Zhang, Litian Zhang +4
The widespread dissemination of fake news on social media has significantly impacted society, resulting in serious consequences. Conventional deep learning methodologies employing…
Collaborative Evolution: Multi-Round Learning Between Large and Small Language Models for Emergent Fake News Detection
Ziyi Zhou, Xiaoming Zhang, Shenghan Tan +2
The proliferation of fake news on social media platforms has exerted a substantial influence on society, leading to discernible impacts and deleterious consequences. Conventional d…
Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems
Bingyu Yan, Zhibo Zhou, Litian Zhang +6
Large language model-based multi-agent systems have recently gained significant attention due to their potential for complex, collaborative, and intelligent problem-solving capabil…
FineFake: A Knowledge-Enriched Dataset for Fine-Grained Multi-Domain Fake News Detection
Ziyi Zhou, Xiaoming Zhang, Litian Zhang +6
Existing benchmarks for fake news detection have significantly contributed to the advancement of models in assessing the authenticity of news content. However, these benchmarks typ…