8 papers · 1 filter
ProAR: Learning Prospective Reasoning with Autoregressive Video Models
Linghui Shen, Tinghui Zhu, Sheng Zhang +1
Autoregressive (AR) video models excel at causal generation, but their reliance on next-chunk prediction confines them to a short-sighted, reactive paradigm. This limitation is par…
VisAnalog: A Diagnostic Suite for Visual Concept Transfer on Natural Images
Zhaonan Li, Kyle R. Chickering, Bangzheng Li +13
A useful test of visual concept learning is not just whether a model can recognize a concept in a single image, but whether it can preserve and manipulate concept-level properties…
Video Models Can Reason with Verifiable Rewards
Tinghui Zhu, Sheng Zhang, James Y. Huang +5
Video diffusion models have made rapid progress in perceptual realism and temporal coherence, but they remain primarily optimized for plausible generation rather than verifiable re…
When Vision Speaks for Sound
Xiaofei Wen, Wenjie Jacky Mo, Xingyu Fu +6
Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual cues to infer or hallucinate…
SafeLens: Deliberate and Efficient Video Guardrails with Fast-and-Slow Screening
Shahriar Kabir Nahin, Hadi Askari, Muhao Chen +1
The rapid growth of online video platforms and AI-generated content has made reliable video guardrails a key challenge for safety and real-world deployment. While most videos can b…
Learning Adaptive Reasoning Paths for Efficient Visual Reasoning
Yixu Huang, Tinghui Zhu, Muhao Chen
Visual reasoning models (VRMs) have recently shown strong cross-modal reasoning capabilities by integrating visual perception with language reasoning. However, they often suffer fr…
Unbiased Visual Reasoning with Controlled Visual Inputs
Zhaonan Li, Shijie Lu, Fei Wang +11
End-to-end Vision-language Models (VLMs) often answer visual questions by exploiting spurious correlations instead of causal visual evidence, and can become more shortcut-prone whe…
Latent Visual Reasoning
Bangzheng Li, Ximeng Sun, Jiang Liu +7
Multimodal Large Language Models (MLLMs) have achieved notable gains in various tasks by incorporating Chain-of-Thought (CoT) reasoning in language spaces. Recent work extends this…