25 citations · 54 across the 28 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.AI2025★ 1 cited
Neutralizing Popularity Bias in LLM-based Recommendation via Counterfactual Reasoning Guidelines
Guanrong Li, Haolin Yang, Xinyu Liu +3
In the era of generative AI, recommender systems are moving from precise prediction to trustworthy generation. Large language models (LLMs) support this shift by inferring user int…
cs.AI2025
Rethinking Relation Extraction: Beyond Shortcuts to Generalization with a Debiased Benchmark
Liang He, Yougang Chu, Zhen Wu +3
Benchmarks are crucial for evaluating machine learning algorithm performance, facilitating comparison and identifying superior solutions. However, biases within datasets can lead m…