Papers by Hongli Xu
An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4 (2025.findings-acl)
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| Challenge: | Recent studies have fine-tuned judge models based on open-source LLMs to evaluate the quality of other LLM. |
| Approach: | They propose to use open-source LLMs to evaluate Large Language Models (LLMs) their empirical results show that the models underperform GPT-4 in several dimensions . |
| Outcome: | The proposed models outperform GPT-4 on several dimensions including generalizability, fairness and adaptability. |
Top-n𝜎: Eliminating Noise in Logit Space for Robust Token Sampling of LLM (2025.acl-long)
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| Challenge: | Existing sampling methods that are sensitive to temperature scaling fail to distinguish between diversity and noise. |
| Approach: | They propose a method that identifies informative tokens by eliminating noise directly in logit space and a new sampling method that is temperature-invariant. |
| Outcome: | The proposed method outperforms existing methods with significant improvements in reasoning and creative writing tasks. |