3 papers
cs.CV2026
What Makes Video World Model Latents Action-Relevant: Prediction over Reconstruction
Jewon Yeom, Hanseul Kim, Jeongjae Park +3
Video world models are increasingly used to provide predictive visual representations, yet it remains unclear which pretraining signals induce action-relevant structure in their la…
cs.CL2026
Models Know Models Best: Evaluation via Model-Preferred Formats
Joonhak Lee, Sungmok Jung, Jongyeon Park +1
Performance of Large Language Models (LLMs) on multiple-choice tasks differs markedly between symbol-based and cloze-style evaluation formats. The observed discrepancies are system…
cs.CL2025
Thunder-NUBench: A Benchmark for LLMs' Sentence-Level Negation Understanding
Yeonkyoung So, Gyuseong Lee, Sungmok Jung +4
Negation is a fundamental linguistic phenomenon that poses ongoing challenges for Large Language Models (LLMs), particularly in tasks requiring deep semantic understanding. Current…