*-PLUIE: Personalisable metric with Llm Used for Improved Evaluation 事件

*-PLUIE: Personalisable metric with Llm Used for Improved Evaluation arXiv:2602.15778v2 Announce Type: replace Abstract: Evaluating the quality of automatically generated text often relies on LLM-as-a-judge (LLM-judge) methods. While effective, these approaches are computationally expensive and require post-processing. To address these limitations, we build upon ParaPLUIE, a perplexity-based LLM-judge metric that estimates confidence over ``Yes/No'' answers without generating text. We introduce