6 papers
UniVideo: Unified Understanding, Generation, and Editing for Videos
Cong Wei, Quande Liu, Zixuan Ye +5
Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain. In this work, we present UniVide…
RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time
Haozhe Wang, Cong Wei, Weiming Ren +3
Most reward models for visual generation reduce rich human judgments to a single unexplained score, discarding the reasoning that underlies preference. We show that teaching reward…
MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks
Jiacheng Chen, Tianhao Liang, Sherman Siu +13
We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500 real-world tasks, to address the highly heterogeneous daily use cases of end users. Our obj…
DisProtEdit: Exploring Disentangled Representations for Multi-Attribute Protein Editing
Max Ku, Sun Sun, Hongyu Guo +1
We introduce DisProtEdit, a controllable protein editing framework that leverages dual-channel natural language supervision to learn disentangled representations of structural and…
MoCha: Towards Movie-Grade Talking Character Synthesis
Cong Wei, Bo Sun, Haoyu Ma +10
Recent advancements in video generation have achieved impressive motion realism, yet they often overlook character-driven storytelling, a crucial task for automated film, animation…
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks
Ziyan Jiang, Rui Meng, Xinyi Yang +3
Embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering. Recently, there has been a surge of inte…