4 papers
When Order Matters: First-Speaker Bias and Mitigation through Personality in Sequential Multi-Agent Debate
Duofeng Xu, Bryan Hooi, Dandan Qiao
Multi-agent debate (MAD) is often used to improve large language model (LLM) reasoning, but sequential debate is rarely a neutral aggregator of agents' opinions. We show that seque…
Cyber-Resilient System Identification for Power Grid through Bayesian Integration
Shimiao Li, Guannan Qu, Bryan Hooi +3
Power grids increasingly need real-time situational awareness under the ever-evolving cyberthreat landscape. Advances in snapshot-based system identification approaches have enable…
Enhancing Multi-Agent Debate System Performance via Confidence Expression
Zijie Lin, Bryan Hooi
Generative Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of tasks. Recent research has introduced Multi-Agent Debate (MAD) systems, whic…
From Long to Short: LLMs Excel at Trimming Own Reasoning Chains
Wei Han, Geng Zhan, Sicheng Yu +2
O1/R1 style large reasoning models (LRMs) signal a substantial leap forward over conventional instruction-following LLMs. By applying test-time scaling to generate extended reasoni…