5 citations · 7 across the 18 of their papers we have counts for
7 papers · 1 filter
Small Models Scout Bottleneck Order for Large-Model Data Control
Seungmin Choi, Jiwon Sung, Muhammad Umer +4
Small proxy models are commonly used to identify data mixtures for larger-scale training. We ask whether their training trajectories reveal another transferable structure: the orde…
Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback
Guijin Son, Jehyun Park, Seyeon Park +2
Computer-aided design (CAD) is the backbone of modern industrial design, yet learned CAD generators still fall short of real engineering pipelines: they neither iterate like engine…
Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs
Guijin Son, Seungone Kim, Catherine Arnett +73
Following the recent achievement of gold-medal performance on the IMO by frontier LLMs, the community is searching for the next meaningful and challenging target for measuring LLM…
KMMMU: Evaluation of Massive Multi-discipline Multimodal Understanding in Korean Language and Context
Nahyun Lee, Guijin Son, Hyunwoo Ko +4
Multimodal evaluation is strengthened when benchmarks reflect the languages, institutions, and disciplinary conventions that shape expert visual reasoning. We introduce KMMMU, a na…
Pushing the Boundaries of Multiple Choice Evaluation to One Hundred Options
Nahyun Lee, Guijin Son
Multiple choice evaluation is widely used for benchmarking large language models, yet near ceiling accuracy in low option settings can be sustained by shortcut strategies that obsc…
Judging What We Cannot Solve: A Consequence-Based Approach for Oracle-Free Evaluation of Research-Level Math
Guijin Son, Donghun Yang, Hitesh Laxmichand Patel +5
Recent progress in reasoning models suggests that generating plausible attempts for research-level mathematics may be within reach, but verification remains a bottleneck, consuming…
What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models
Dasol Choi, Guijin Son, Hanwool Lee +7
Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries are often informal and underspecified. U…