63 citations · 248 across the 35 of their papers we have counts for
5 papers · 1 filter
Compositional Physical Reasoning of Objects and Events from Videos
Zhenfang Chen, Shilong Dong, Kexin Yi +5
Understanding and reasoning about objects' physical properties in the natural world is a fundamental challenge in artificial intelligence. While some properties like colors and sha…
FlexAttention for Efficient High-Resolution Vision-Language Models
Junyan Li, Delin Chen, Tianle Cai +5
Current high-resolution vision-language models encode images as high-resolution image tokens and exhaustively take all these tokens to compute attention, which significantly increa…
SOK-Bench: A Situated Video Reasoning Benchmark with Aligned Open-World Knowledge
Andong Wang, Bo Wu, Sunli Chen +5
Learning commonsense reasoning from visual contexts and scenes in real-world is a crucial step toward advanced artificial intelligence. However, existing video reasoning benchmarks…
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
Zhicheng Zheng, Xin Yan, Zhenfang Chen +4
We introduce the Continuum Physical Dataset (ContPhy), a novel benchmark for assessing machine physical commonsense. ContPhy complements existing physical reasoning benchmarks by e…
Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble
Shun Zhang, Zhenfang Chen, Sunli Chen +3
Reinforcement Learning from Human Feedback (RLHF) is a widely adopted approach for aligning large language models with human values. However, RLHF relies on a reward model that is…