most citedRelative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts

2 citations · 2 across the 6 of their papers we have counts for

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cs.CL2025

Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs

Feng Hong, Geng Yu, Yushi Ye +5

Diffusion Large Language Models (DLLMs) have emerged as a compelling alternative to Autoregressive models, designed for fast parallel generation. However, existing DLLMs are plague…

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…