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20242026
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cs.CL2026

K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts

Nahyun Lee, Dongkeun Yoon, Guijin Son +12

Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, but Korean agentic benchmarks…

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.CL2024

A 2-step Framework for Automated Literary Translation Evaluation: Its Promises and Pitfalls

Sheikh Shafayat, Dongkeun Yoon, Woori Jang +3

In this work, we propose and evaluate the feasibility of a two-stage pipeline to evaluate literary machine translation, in a fine-grained manner, from English to Korean. The result…

cs.CL20242 cited

MM-Eval: A Multilingual Meta-Evaluation Benchmark for LLM-as-a-Judge and Reward Models

Guijin Son, Dongkeun Yoon, Juyoung Suk +7

As Large Language Models (LLMs) are now capable of producing fluent and coherent content in languages other than English, it is not imperative to precisely evaluate these non-Engli…

cs.CL2024

The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models

Seungone Kim, Juyoung Suk, Ji Yong Cho +29

As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently as…