2 citations · 3 across the 8 of their papers we have counts for
9 papers
Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment
Jiajia Li, Xiaoyu Wen, Zhongtian Ma +3
The growing capabilities of large language models (LLMs) have driven their widespread deployment across diverse domains, even in potentially high-risk scenarios. Despite advances i…
Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation
Zhiyao Cui, Chenxu Wang, Shuyue Hu +4
Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints. For such structured multimodal…
Adaptive Theory of Mind for LLM-based Multi-Agent Coordination
Chunjiang Mu, Ya Zeng, Qiaosheng Zhang +6
Theory of Mind (ToM) refers to the ability to reason about others' mental states, and higher-order ToM involves considering that others also possess their own ToM. Equipping large…
PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration
Xin Wang, Zhiyao Cui, Hao Li +10
Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with perso…
Reputation as a Solution to Cooperation Collapse in LLM-based MASs
Siyue Ren, Wanli Fu, Xinkun Zou +5
Cooperation has long been a fundamental topic in both human society and AI systems. However, recent studies indicate that the collapse of cooperation may emerge in multi-agent syst…
Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity
Hangfan Zhang, Zhiyao Cui, Jianhao Chen +5
Multi-agent debate (MAD) has gained significant attention as a promising line of research to improve the factual accuracy and reasoning capabilities of large language models (LLMs)…
Overcoming the Machine Penalty with Imperfectly Fair AI Agents
Zhen Wang, Ruiqi Song, Chen Shen +7
Despite rapid technological progress, effective human-machine cooperation remains a significant challenge. Humans tend to cooperate less with machines than with fellow humans, a ph…
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning
Qiaosheng Zhang, Chenjia Bai, Shuyue Hu +2
This work designs and analyzes a novel set of algorithms for multi-agent reinforcement learning (MARL) based on the principle of information-directed sampling (IDS). These algorith…
Emergence of Social Norms in Generative Agent Societies: Principles and Architecture
Siyue Ren, Zhiyao Cui, Ruiqi Song +2
Social norms play a crucial role in guiding agents towards understanding and adhering to standards of behavior, thus reducing social conflicts within multi-agent systems (MASs). Ho…