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20242026
most citedScience-T2I: Addressing Scientific Illusions in Image Synthesis

1 citations · 2 across the 9 of their papers we have counts for

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cs.CV2025

SAGE: Training Smart Any-Horizon Agents for Long Video Reasoning with Reinforcement Learning

Jitesh Jain, Jialuo Li, Zixian Ma +7

As humans, we are natural any-horizon reasoners, i.e., we can decide whether to iteratively skim long videos or watch short ones in full when necessary for a given task. With this…

cs.CV2025

Divide, then Ground: Adapting Frame Selection to Query Types for Long-Form Video Understanding

Jialuo Li, Bin Li, Jiahao Li +1

The application of Large Multimodal Models (LMMs) to long-form video understanding is constrained by limited context lengths and the computationally prohibitive cost of processing…

cs.CV2025

PAI-Bench: A Comprehensive Benchmark For Physical AI

Fengzhe Zhou, Jiannan Huang, Jialuo Li +2

Physical AI aims to develop models that can perceive and predict real-world dynamics; yet, the extent to which current multi-modal large language models and video generative models…

cs.CV2025

ChronosObserver: Taming 4D World with Hyperspace Diffusion Sampling

Qisen Wang, Yifan Zhao, Peisen Shen +2

Although prevailing camera-controlled video generation models can produce cinematic results, lifting them directly to the generation of 3D-consistent and high-fidelity time-synchro…

cs.CV2025★ 1 cited

Science-T2I: Addressing Scientific Illusions in Image Synthesis

Jialuo Li, Wenhao Chai, Xingyu Fu +2

Current image generation models produce visually compelling but scientifically implausible images, exposing a fundamental gap between visual fidelity and physical realism. In this…