8 papers
Predicting LLM Reasoning Performance with Small Proxy Model
Woosung Koh, Juyoung Suk, Sungjun Han +2
Given the prohibitive cost of pre-training large language models, it is essential to leverage smaller proxy models to optimize datasets before scaling up. However, this approach be…
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…
Evaluating Language Models as Synthetic Data Generators
Seungone Kim, Juyoung Suk, Xiang Yue +7
Given the increasing use of synthetic data in language model (LM) post-training, an LM's ability to generate high-quality data has become nearly as crucial as its ability to solve…
LLM-as-an-Interviewer: Beyond Static Testing Through Dynamic LLM Evaluation
Eunsu Kim, Juyoung Suk, Seungone Kim +3
We introduce LLM-as-an-Interviewer, a novel paradigm for evaluating large language models (LLMs). This approach leverages multi-turn interactions where the LLM interviewer actively…
Trillion 7B Technical Report
Sungjun Han, Juyoung Suk, Suyeong An +5
We introduce Trillion-7B, the most token-efficient Korean-centric multilingual LLM available. Our novel Cross-lingual Document Attention (XLDA) mechanism enables highly efficient a…
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…