1 citations · 1 across the 5 of their papers we have counts for
5 papers
SynMulti: Synthetic-to-Real Learning for Multimodal Video Understanding
Tanzila Rahman, Renjie Liao, Leonid Sigal
Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object counting, question answering, an…
Scaling Generative Verifiers For Natural Language Mathematical Proof Verification And Selection
Sadegh Mahdavi, Branislav Kisacanin, Shubham Toshniwal +6
Large language models have achieved remarkable success on final-answer mathematical problems, largely due to the ease of applying reinforcement learning with verifiable rewards. Ho…
Multi-scale Latent Point Consistency Models for 3D Shape Generation
Bi'an Du, Wei Hu, Renjie Liao
Consistency Models (CMs) have significantly accelerated the sampling process in diffusion models, yielding impressive results in synthesizing high-resolution images. To explore and…
From Graph Diffusion to Graph Classification
Jia Jun Cheng Xian, Sadegh Mahdavi, Renjie Liao +1
Generative models such as diffusion models have achieved remarkable success in state-of-the-art image and text tasks. Recently, score-based diffusion models have extended their suc…
Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing
Bi'an Du, Xiang Gao, Wei Hu +1
Generative 3D part assembly involves understanding part relationships and predicting their 6-DoF poses for assembling a realistic 3D shape. Prior work often focus on the geometry o…