1 citations · 1 across the 4 of their papers we have counts for
4 papers
COLLATOR: Compositional Multi-Agent Orchestration with Counterfactual Reinforcement Learning
Xudong Chen, Yixin Liu, Hua Wei +1
Large language models (LLMs) provide a flexible foundation for multi-agent systems, but their effectiveness and computational cost depend critically on orchestration design. Across…
Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning
Alan Li, Yixin Liu, Arpan Sarkar +2
Scientific problem solving poses unique challenges for LLMs, requiring both deep domain knowledge and the ability to apply such knowledge through complex reasoning. While automated…
COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
Yixin Liu, Argyris Oikonomou, Weiqiang Zheng +2
Many alignment methods, including reinforcement learning from human feedback (RLHF), rely on the Bradley-Terry reward assumption, which is not always sufficient to capture the full…
Calibrating Long-form Generations from Large Language Models
Yukun Huang, Yixin Liu, Raghuveer Thirukovalluru +2
To enhance Large Language Models' (LLMs) reliability, calibration is essential -- the model's assessed confidence scores should align with the actual likelihood of its responses be…