82 citations · 182 across the 16 of their papers we have counts for
20 papers
Rectified Flow For Structure Based Drug Design
Daiheng Zhang, Chengyue Gong, Qiang Liu
Deep generative models have achieved tremendous success in structure-based drug design in recent years, especially for generating 3D ligand molecules that bind to specific protein…
Fast Point Cloud Generation with Straight Flows
Lemeng Wu, Dilin Wang, Chengyue Gong +6
Diffusion models have emerged as a powerful tool for point cloud generation. A key component that drives the impressive performance for generating high-quality samples from noise i…
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models
Shujian Zhang, Chengyue Gong, Xingchao Liu
Retriever-reader models achieve competitive performance across many different NLP tasks such as open question answering and dialogue conversations. In this work, we notice these mo…
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Xingchao Liu, Chengyue Gong, Qiang Liu
We present rectified flow, a surprisingly simple approach to learning (neural) ordinary differential equation (ODE) models to transport between two empirically observed distributio…
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity
Chengyue Gong, Lemeng Wu, Qiang Liu
Although traditional optimization methods focus on finding a single optimal solution, most objective functions in modern machine learning problems, especially those in deep learnin…
Learning with Different Amounts of Annotation: From Zero to Many Labels
Shujian Zhang, Chengyue Gong, Eunsol Choi
Training NLP systems typically assumes access to annotated data that has a single human label per example. Given imperfect labeling from annotators and inherent ambiguity of langua…