30 citations · 31 across the 7 of their papers we have counts for
8 papers
VisualTrust: Video Reasoning under On-Screen Claim Framing
Huachao Zhu, Junjielong Xu, Sicheng Li +5
On-screen text can describe what a video shows, or it can frame what the video is supposed to mean. Current benchmarks treat both alike, testing whether a model can read the text r…
DramaChain Bench: An End-to-End Benchmark for Short-Drama Generation
Haoyuan Shi, Mingtao Chen, Shuo Jiang +12
Commercial short-drama production follows a multi-stage chain: script, storyboard, keyframe imagery, shot-level video, and the finished short drama. Most existing benchmarks evalua…
VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes
Jingru Chen, Yiming Liu, Mingtao Chen +5
Frontier multimodal large language models (MLLMs) have been reported to achieve over 90\% accuracy on fine-grained perception benchmarks. However, such scores do not necessarily im…
TAGRPO: Boosting GRPO on Image-to-Video Generation with Direct Trajectory Alignment
Jin Wang, Jianxiang Lu, Guangzheng Xu +10
Recent studies have demonstrated the efficacy of integrating Group Relative Policy Optimization (GRPO) into flow matching models, particularly for text-to-image and text-to-video g…
Q-Save: Towards Scoring and Attribution for Generated Video Evaluation
Xiele Wu, Zicheng Zhang, Mingtao Chen +12
Evaluating AI-generated video (AIGV) quality hinges on three crucial dimensions: visual quality, dynamic quality, and text-video alignment. While numerous evaluation datasets and a…
Rethinking KL Regularization in RLHF: From Value Estimation to Gradient Optimization
Kezhao Liu, Jason Klein Liu, Mingtao Chen +1
Reinforcement Learning from Human Feedback (RLHF) leverages a Kullback-Leibler (KL) divergence loss to stabilize training and prevent overfitting. However, in methods such as GRPO,…
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
Zhimin Li, Jianwei Zhang, Qin Lin +42
We present Hunyuan-DiT, a text-to-image diffusion transformer with fine-grained understanding of both English and Chinese. To construct Hunyuan-DiT, we carefully design the transfo…
Efficient Teacher: Semi-Supervised Object Detection for YOLOv5
Bowen Xu, Mingtao Chen, Wenlong Guan +1
Semi-Supervised Object Detection (SSOD) has been successful in improving the performance of both R-CNN series and anchor-free detectors. However, one-stage anchor-based detectors l…