3 papers
cs.CL2026
Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification
Weili Shi, Dongliang Guo, Lehan Yang +3
Large language models have demonstrated impressive performance across a variety of reasoning tasks. However, their problem-solving ability often declines on more complex tasks due…
cs.CV2025
Unified Dense Prediction of Video Diffusion
Lehan Yang, Lu Qi, Xiangtai Li +3
We present a unified network for simultaneously generating videos and their corresponding entity segmentation and depth maps from text prompts. We utilize colormap to represent ent…
cs.CV2025
VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion
Lehan Yang, Jincen Song, Tianlong Wang +4
We propose a new task, video referring matting, which obtains the alpha matte of a specified instance by inputting a referring caption. We treat the dense prediction task of mattin…