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MILE-RefHumEval: A Reference-Free, Multi-Independent LLM Framework for Human-Aligned Evaluation

arXiv 2602.09624 ↗First posted 10 Feb 2026cs.CLcited by 0

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Abstract (arXiv)

We introduce MILE-RefHumEval, a reference-free framework for evaluating Large Language Models (LLMs) without ground-truth annotations or evaluator coordination. It leverages an ensemble of independently prompted evaluators guided by a human-aligned schema, supporting both discrete and continuous scoring judgement. With task-specific prompts from best candidate selection, summarization and image captioning to dialogue, MILE-RefHumEval provides flexible, interpretable, and scalable assessments. Experiments show it aligns closely with human judgments, outperforms prior methods, and reduces computational overhead, offering an efficient, robust, and human-aligned solution for real-world LLM evaluation.

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19 of 31 references.

References · 19

  1. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  2. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
  3. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
  4. 2021LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairscited by 1,544
  5. 2023Large Language Models are not Fair Evaluatorscited by 1,050
  6. 2023ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debatecited by 724
  7. 2020SummEval: Re-evaluating Summarization Evaluationcited by 666
  8. 2023JudgeLM: Fine-tuned Large Language Models are Scalable Judgescited by 351
  9. 2024Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Modelscited by 301
  10. 2024MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmarkcited by 281
  11. 2020USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generationcited by 186
  12. 2023Benchmarking Foundation Models with Language-Model-as-an-Examinercited by 172
7 more
  1. 2024Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreementcited by 99
  2. 2023Towards Reasoning in Large Language Models via Multi-Agent Peer Review Collaborationcited by 48
  3. 2024Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussionscited by 40
  4. 2024Code Comprehension then Auditing for Unsupervised LLM Evaluationcited by 31
  5. 2024An Empirical Analysis on Large Language Models in Debate Evaluationcited by 20
  6. 2019Quality Estimation for Image Captions Based on Large-scale Human Evaluationscited by 17
  7. 2023Fusion-Eval: Integrating Assistant Evaluators with LLMscited by 6

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