1 citations · 3 across the 4 of their papers we have counts for
7 papers
BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations
Weixi Feng, Chao Liu, Sifei Liu +3
Existing video generation models struggle to follow complex text prompts and synthesize multiple objects, raising the need for additional grounding input for improved controllabili…
T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design
Jiachen Li, Qian Long, Jian Zheng +4
In this paper, we focus on enhancing a diffusion-based text-to-video (T2V) model during the post-training phase by distilling a highly capable consistency model from a pretrained T…
MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos
Xuehai He, Weixi Feng, Kaizhi Zheng +11
Multimodal Language Language Models (MLLMs) demonstrate the emerging abilities of "world models" -- interpreting and reasoning about complex real-world dynamics. To assess these ab…
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning
Danqing Wang, Antonis Antoniades, Kha-Dinh Luong +6
Counterfactual explanations of Graph Neural Networks (GNNs) offer a powerful way to understand data that can naturally be represented by a graph structure. Furthermore, in many dom…
TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation
Weixi Feng, Jiachen Li, Michael Saxon +3
Video generation has many unique challenges beyond those of image generation. The temporal dimension introduces extensive possible variations across frames, over which consistency…
BPO: Staying Close to the Behavior LLM Creates Better Online LLM Alignment
Wenda Xu, Jiachen Li, William Yang Wang +1
Direct alignment from preferences (DAP) has emerged as a promising paradigm for aligning large language models (LLMs) to human desiderata from pre-collected, offline preference dat…