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From the 1 of 7 linked papers with an AI index.

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20242026
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cs.CL2026

Scaling Evaluation-time Compute with Reasoning Models as Evaluators

Seungone Kim, Ian Wu, Jinu Lee +8

The paper studies how using larger, chain‑of‑thought reasoning language models as evaluators—by allocating more test‑time compute—can improve the accuracy of evaluating and reranki…

cs.CL2026

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists

Seungone Kim, Dongkeun Yoon, Kiril Gashteovski +55

With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remain in question: many scientis…

cs.CL2025

M-Prometheus: A Suite of Open Multilingual LLM Judges

José Pombal, Dongkeun Yoon, Patrick Fernandes +5

The use of language models for automatically evaluating long-form text (LLM-as-a-judge) is becoming increasingly common, yet most LLM judges are optimized exclusively for English,…

cs.CL2025

Better Instruction-Following Through Minimum Bayes Risk

Ian Wu, Patrick Fernandes, Amanda Bertsch +3

General-purpose LLM judges capable of human-level evaluation provide not only a scalable and accurate way of evaluating instruction-following LLMs but also new avenues for supervis…

cs.CL2024

Synthetic Multimodal Question Generation

Ian Wu, Sravan Jayanthi, Vijay Viswanathan +4

Multimodal Retrieval Augmented Generation (MMRAG) is a powerful approach to question-answering over multimodal documents. A key challenge with evaluating MMRAG is the paucity of hi…