Publications

• ICONS: Influence Consensus for Vision-Language Data Selection
  Xindi Wu, Mengzhou Xia, Rulin Shao, Zhiwei Deng, Pang Wei Koh, and Olga Russakovsky
  arXiv 2024;
  [arXiv]
  


• Influential Language Data Selection via Gradient Trajectory Pursuit
  Zhiwei Deng, Tao Li, and Yang Li
  arXiv 2024;
  [arXiv]
  


• Perceptual Group Tokenizer: Building Perception with Iterative Grouping
  Zhiwei Deng, Ting Chen, and Yang Li
  ICLR 2024;
  [arXiv]
  


• A Label is Worth a Thousand Images in Dataset Distillation
  Tian Qin, Zhiwei Deng, and David Alvarez-Melis
  NeurIPS 2024;
  [arXiv]
  


• Devil's Advocate: Anticipatory Reflection for LLM Agents
  Haoyu Wang, Tao Li, Zhiwei Deng, Dan Roth, and Yang Li
  EMNLP 2024;
  [arXiv]
  


• What is Dataset Distillation Learning?
  William Yang, Ye Zhu, Zhiwei Deng, and Olga Russakovsky
  ICML 2024;
  [arXiv] [Code]
  


• Vision-Language Dataset Distillation
  Xindi Wu, Byron Zhang, Zhiwei Deng, and Olga Russakovsky
  TMLR, ECCV Dataset Distillation Workshop (Best Paper Award) 2024;
  Website | arXiv | TMLR Paper Site | Video (45 mins) | Slides(canva, pdf) | Poster | Code
  


• Boundary Guided Learning-Free Semantic Control with Diffusion Models
  Ye Zhu, Yu Wu, Zhiwei Deng, Olga Russakovsky, and Yan Yan
  NeurIPS 2023;
  [arXiv] [Code] project
  


• Remember the Past: Distilling Datasets into Addressable Memories for Neural Networks
  Zhiwei Deng and Olga Russakovsky
  NeurIPS 2022;
  [arXiv] [Code]
  


• Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
  Zhiwei Deng, Karthik Narasimhan, and Olga Russakovsky
  NeurIPS 2020;
  [arXiv]
  


• BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps
  Wang (Bill) Zhu*, Hexiang Hu*, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, and Fei Sha
  ACL 2020 (Oral);
  [arXiv]
  


• Take the Scenic Route: Improving Generalization in Vision-and-Language Navigation
  Felix Yu, Zhiwei Deng, Karthik Narasimhan, and Olga Russakovsky
  CVPR 2020, Visual Learning with Limited Labels Workshop 2020 (Oral);
  [arXiv]
  


• Continuous Graph Flow
  Zhiwei Deng*, Megha Nawhal*, Lili Meng, and Greg Mori
  ICML 2020, Workshop on Graph Representation Learning and Beyond 2020;
  [arXiv] [Code]
  


• Policy Message Passing: Modeling Trajectories for Probabilistic Graph Inference
  Zhiwei Deng, Xingguo Li, and Greg Mori
  [paper]
  


• Talking With Hands 16.2M: A Large-Scale Dataset of Synchronized Body-Finger Motion and Audio for Conversational Motion Analysis and Synthesis
  Gilwoo Lee, Zhiwei Deng, Shugao Ma, Takaaki Shiratori, Siddhartha S. Srinivasa, and Yaser Sheikh
  ICCV 2019;
  [paper] [Code]
  


• Learning Structured Inference Neural Networks with Label Relations
  Nelson Nauata, Hexiang Hu, Guang-tong Zhou, Zhiwei Deng, Zicheng Liao, and Greg Mori
  T-PAMI 2019;
  [arXiv]
  


• Probabilistic Neural Programmed Networks for Scene Generation
  Zhiwei Deng, Jiacheng Chen, Yifang Fu, and Greg Mori
  NeurIPS 2018 (Spotlight);
  [arXiv]
  


• Sparsely Aggregated Convolutional Networks
  Ligeng Zhu, Ruizhi Deng, Michael Maire, Zhiwei Deng, and Greg Mori
  ECCV 2018;
  [arXiv] [code]
  


• Factorized Variational Autoencoders for Modeling Audience Reactions to Movies
  Zhiwei Deng, and Greg Mori
  CVPR 2017;
  [paper] (Press Coverage CBC News | PHYS.ORG | Caltech News)
  


• Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition
  Zhiwei Deng, Arash Vahdat, Hexiang Hu, and Greg Mori
  CVPR 2016;
  [arXiv] [webpage] [Extended Collective Activity Dataset: train-test split]
  


• Deep Structured Models For Group Activity Recognition
  Zhiwei Deng, Mengyao Zhai, Lei Chen, Yuhao Liu, Srikanth Muralidharan, Mehrsan Roshtkhari, and Greg Mori
  BMVC 2015 (Oral);
  [arXiv]