55 citations · 63 across the 10 of their papers we have counts for
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cs.AI2025★ 1 cited
TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them
Yidong Wang, Yunze Song, Tingyuan Zhu +11
The adoption of Large Language Models (LLMs) as automated evaluators (LLM-as-a-judge) has revealed critical inconsistencies in current evaluation frameworks. We identify two fundam…
cs.CL2025
Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future
Yidong Wang, Xin Wang, Cunxiang Wang +9
Self-Rewarding Language Models propose an architecture in which the Large Language Models(LLMs) both generates responses and evaluates its own outputs via LLM-as-a-Judge prompting,…
cs.CL2025★ 1 cited
RewardAnything: Generalizable Principle-Following Reward Models
Zhuohao Yu, Jiali Zeng, Weizheng Gu +7
Reward Models, essential for guiding Large Language Model optimization, are typically trained on fixed preference datasets, resulting in rigid alignment to single, implicit prefere…