3 citations · 7 across the 17 of their papers we have counts for
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cs.CL2026
System1-Arena: Which Decisions Can Be Left to System 1?
Tianyu Chen, Xinyang Liu, Ruyi An +2
Large language models (LLMs) often make discrete decisions, such as flagging phishing or escalating to a human. System-1 models, such as Jev and the OpenAI Decisions API, return pr…
cs.CL2024
Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment
Yueqin Yin, Zhendong Wang, Yujia Xie +2
Traditional language model alignment methods, such as Direct Preference Optimization (DPO), are limited by their dependence on static, pre-collected paired preference data, which h…
cs.CL2024★ 2 cited
Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts
Yueqin Yin, Zhendong Wang, Yi Gu +3
In the field of large language models (LLMs), aligning models with the diverse preferences of users is a critical challenge. Direct Preference Optimization (DPO) has played a key r…