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20242026
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cs.CL2025

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…

cs.CL2024

Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models

Seungone Kim, Juyoung Suk, Shayne Longpre +7

Proprietary LMs such as GPT-4 are often employed to assess the quality of responses from various LMs. However, concerns including transparency, controllability, and affordability s…

cs.CL2024

How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?

Seongyun Lee, Geewook Kim, Jiyeon Kim +4

Vision-Language adaptation (VL adaptation) transforms Large Language Models (LLMs) into Large Vision-Language Models (LVLMs) for multimodal tasks, but this process often compromise…

cs.CL2024

Aligning to Thousands of Preferences via System Message Generalization

Seongyun Lee, Sue Hyun Park, Seungone Kim +1

Although humans inherently have diverse values, current large language model (LLM) alignment methods often assume that aligning LLMs with the general public's preferences is optima…

cs.CL2024

Hierarchical Deconstruction of LLM Reasoning: A Graph-Based Framework for Analyzing Knowledge Utilization

Miyoung Ko, Sue Hyun Park, Joonsuk Park +1

Despite the advances in large language models (LLMs), how they use their knowledge for reasoning is not yet well understood. In this study, we propose a method that deconstructs co…