1 citations · 2 across the 24 of their papers we have counts for
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Multi-Objective Exploration and Preference Optimization via Mutual Information
Hongyan Xie, Yikun Ban, Ruiyu Fang +4
Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicting preference dimensions. Cu…
Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process
Zhijun Chen, Zeyu Ji, Qianren Mao +12
We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for each query, harnessing the collective…
UniARM: Towards a Unified Autoregressive Reward Model for Multi-Objective Test-Time Alignment
Hongyan Xie, Yikun Ban, Ruiyu Fang +6
Multi-objective alignment aims to align LLM responses with multiple human preference objectives. Among existing methods, guiding the generation of frozen LLMs through autoregressiv…
Mitigating Spurious Correlations Between Question and Answer via Chain-of-Thought Correctness Perception Distillation
Hongyan Xie, Yitong Yao, Yikun Ban +6
Large language models (LLMs) excel at reasoning tasks but are expensive to deploy. Thus small language models (SLMs) are fine-tuned on CoT data generated by LLMs to copy LLMs' abil…