5 papers
Grid-Bench: Can LLMs Predict How Discrete Worlds Change?
Zixiang Xu, Zirui Song, Wanrong Zheng +16
Spatial instructions describe how to move objects, transform regions, or modify their surroundings. When several operations are applied in sequence, each acts on a configuration sh…
Shorter, but Still Trustworthy? An Empirical Study of Chain-of-Thought Compression
Lingjie Zeng, Xiaofan Chen, Yanbo Wang +1
Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, yet existing evaluations focus alm…
Exposing Cross-Modal Consistency for Fake News Detection in Short-Form Videos
Chong Tian, Yu Wang, Chenxu Yang +5
Short-form video platforms are major channels for news but also fertile ground for multimodal misinformation where each modality appears plausible alone yet cross-modal relationshi…
A Fano-Style Accuracy Upper Bound for LLM Single-Pass Reasoning in Multi-Hop QA
Kaiyang Wan, Lang Gao, Honglin Mu +3
Multi-Hop Question Answering (MHQA) requires integrating dispersed, interdependent evidence through sequential reasoning under noise. This task is challenging for LLMs as they have…
VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration
Jiahui Geng, Qing Li, Zongxiong Chen +7
The rapid advancement of vision-language models (VLMs) has brought a lot of attention to their safety alignment. However, existing methods have primarily focused on model undersafe…