Author

Jae Sung Park

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Preprint Aug 2026

Ask-E: An Environment for Calibrated Question Generation

Today, we improve models by training and evaluating them on problems at the frontier of their abilities. Creating such problems is itself a demanding task, requiring the ability to probe model limits and generalize beyond existing question distributions. It also means placing problems at a precise difficulty level, whi...

Sarah M. Pratt, Jae Sung Park, Scott Geng et al. · 0 citations

AutoJudger : An Adaptive Evaluation Framework for Efficient Benchmarking of MLLMs

This work introduces A 2 -Judger, a novel MLLM-based A gentic instantiation of A uto Judger equipped with semantic-aware retrieval and dynamic memory that significantly improves sample efficiency while maintaining reliable evaluation results.

Xuanwen Ding, Chengjun Pan, Zejun Li et al. · 0 citations