7 papers
OccluRank: Controllable Occlusion-Aware Layout-to-Image Generation by Adding Just an Ordinal Rank
Wenyang Hong, Yuan Wang, Yanbin Hao +5
Layout-to-image generation enables explicit spatial control through bounding-box layouts, yet bounding boxes specify only instance locations and cannot represent their occlusion or…
Uni-AdaVD: Universal Concept Erasure for Visual Generation via Orthogonal Value Decomposition
Qifan Zhou, Yuan Wang, Yanbin Hao +4
Visual generative models inevitably absorb undesirable concepts from uncurated pretraining data, making concept erasure essential for safe deployment. Existing erasure methods, how…
Think, then Score: Decoupled Reasoning and Scoring for Video Reward Modeling
Yuan Wang, Ouxiang Li, Yulong Xu +8
Recent advances in generative video models are increasingly driven by post-training and test-time scaling, both of which critically depend on the quality of video reward models (RM…
Beyond Where to Look: Trajectory-Guided Reinforcement Learning for Multimodal RLVR
Jinda Lu, Junkang Wu, Jinghan Li +6
Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) for multimodal large language models (MLLMs) have mainly focused on improving final answer correctness and…
Thinking with Frames: Generative Video Distortion Evaluation via Frame Reward Model
Yuan Wang, Borui Liao, Huijuan Huang +5
Recent advances in video reward models and post-training strategies have improved text-to-video (T2V) generation. While these models typically assess visual quality, motion quality…
Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters
Yuan Wang, Ouxiang Li, Tingting Mu +4
Recent success of text-to-image (T2I) generation and its increasing practical applications, enabled by diffusion models, require urgent consideration of erasing unwanted concepts,…
Densely Distilling Cumulative Knowledge for Continual Learning
Zenglin Shi, Pei Liu, Tong Su +4
Continual learning, involving sequential training on diverse tasks, often faces catastrophic forgetting. While knowledge distillation-based approaches exhibit notable success in pr…