Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition. - Zhiwei Deng; Arash Vahdat; Hexiang Hu; Greg Mori (CVPR, 2016)

Learning Structured Inference Neural Networks with Label Relations. - Hexiang Hu; Guang-Tong Zhou; Zhiwei Deng; Zicheng Liao; Greg Mori (CVPR, 2016)

Recalling Holistic Information for Semantic Segmentation. - Hexiang Hu; Zhiwei Deng; Guang-Tong Zhou; Fei Sha; Greg Mori (CoRR, 2016)

FastMask: Segment Object Multi-scale Candidates in One Shot. - Hexiang Hu; Shiyi Lan; Yuning Jiang 001; Zhimin Cao; Fei Sha (CoRR, 2016)

FastMask: Segment Multi-scale Object Candidates in One Shot. - Hexiang Hu; Shiyi Lan; Yuning Jiang 001; Zhimin Cao; Fei Sha (CVPR, 2017)

LabelBank: Revisiting Global Perspectives for Semantic Segmentation. - Hexiang Hu; Zhiwei Deng; Guang-Tong Zhou; Fei Sha; Greg Mori (CoRR, 2017)

Multi-Task Learning for Sequence Tagging: An Empirical Study. - Soravit Changpinyo; Hexiang Hu; Fei Sha (COLING, 2018)

Cross-Dataset Adaptation for Visual Question Answering. - Wei-Lun Chao; Hexiang Hu; Fei Sha (CVPR, 2018)

Learning Answer Embeddings for Visual Question Answering. - Hexiang Hu; Wei-Lun Chao; Fei Sha (CVPR, 2018)

Compressed Video Action Recognition. - Chao-Yuan Wu; Manzil Zaheer; Hexiang Hu; R. Manmatha; Alexander J. Smola; Philipp Krähenbühl (CVPR, 2018)

Cross-Modal and Hierarchical Modeling of Video and Text. - Bowen Zhang 002; Hexiang Hu; Fei Sha (ECCV (13), 2018)

Being Negative but Constructively: Lessons Learnt from Creating Better Visual Question Answering Datasets. - Wei-Lun Chao; Hexiang Hu; Fei Sha (NAACL-HLT, 2018)

Synthesize Policies for Transfer and Adaptation across Tasks and Environments. - Hexiang Hu; Liyu Chen; Boqing Gong; Fei Sha (NeurIPS, 2018)

Learning Embedding Adaptation for Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CoRR, 2018)

Toward Multimodal Model-Agnostic Meta-Learning. - Risto Vuorio; Shao-Hua Sun; Hexiang Hu; Joseph J. Lim (CoRR, 2018)

Engaging Image Captioning via Personality. - Kurt Shuster 001; Samuel Humeau 001; Hexiang Hu; Antoine Bordes; Jason Weston (CVPR, 2019)

Evaluating Text-to-Image Matching using Binary Image Selection (BISON). - Hexiang Hu; Ishan Misra; Laurens van der Maaten (ICCV Workshops, 2019)

Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation. - Risto Vuorio; Shao-Hua Sun; Hexiang Hu; Joseph J. Lim (NeurIPS, 2019)

Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding. - Hexiang Hu; Ishan Misra; Laurens van der Maaten (CoRR, 2019)

Synthesized Policies for Transfer and Adaptation across Tasks and Environments. - Hexiang Hu; Liyu Chen; Boqing Gong; Fei Sha (CoRR, 2019)

Learning Classifier Synthesis for Generalized Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CoRR, 2019)

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. - Wang Zhu 001; Hexiang Hu; Jiacheng Chen; Zhiwei Deng; Vihan Jain; Eugene Ie; Fei Sha (ACL, 2020)

Few-Shot Learning via Embedding Adaptation With Set-to-Set Functions. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan; Fei Sha (CVPR, 2020)

Learning to Represent Image and Text with Denotation Graph. - Bowen Zhang 002; Hexiang Hu; Vihan Jain; Eugene Ie; Fei Sha (EMNLP (1), 2020)

Visual Storytelling via Predicting Anchor Word Embeddings in the Stories. - Bowen Zhang 002; Hexiang Hu; Fei Sha (CoRR, 2020)

A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus. - Bowen Zhang 002; Hexiang Hu; Joonseok Lee; Ming Zhao; Sheide Chammas; Vihan Jain; Eugene Ie; Fei Sha (CoRR, 2020)

Structured Label Inference for Visual Understanding. - Nelson Nauata; Hexiang Hu; Guang-Tong Zhou; Zhiwei Deng; Zicheng Liao; Greg Mori (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Learning the Best Pooling Strategy for Visual Semantic Embedding. - Jiacheng Chen; Hexiang Hu; Hao Wu 011; Yuning Jiang 001; Changhu Wang (CVPR, 2021)

Visually Grounded Concept Composition. - Bowen Zhang 002; Hexiang Hu; Linlu Qiu; Peter Shaw 004; Fei Sha (EMNLP (Findings), 2021)

Systematic Generalization on gSCAN: What is Nearly Solved and What is Next? - Linlu Qiu; Hexiang Hu; Bowen Zhang 002; Peter Shaw 004; Fei Sha (EMNLP (1), 2021)

MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. - Cheng Zhang 014; Tai-Yu Pan; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (ICCV, 2021)

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation. - Tai-Yu Pan; Cheng Zhang 014; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (NeurIPS, 2021)

A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection. - Cheng Zhang 014; Tai-Yu Pan; Yandong Li; Hexiang Hu; Dong Xuan; Soravit Changpinyo; Boqing Gong; Wei-Lun Chao (CoRR, 2021)

Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning. - Han-Jia Ye; Hexiang Hu; De-Chuan Zhan (Int. J. Comput. Vis., 2021)

MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text. - Wenhu Chen; Hexiang Hu; Xi Chen 071; Pat Verga; William W. Cohen (EMNLP, 2022)

Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions? - Yang Chen; Hexiang Hu; Yi Luan; Haitian Sun; Soravit Changpinyo; Alan Ritter; Ming-Wei Chang (EMNLP, 2023)

Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities. - Hexiang Hu; Yi Luan; Yang Chen; Urvashi Khandelwal; Mandar Joshi; Kenton Lee; Kristina Toutanova; Ming-Wei Chang (ICCV, 2023)

PreSTU: Pre-Training for Scene-Text Understanding. - Jihyung Kil; Soravit Changpinyo; Xi Chen 071; Hexiang Hu; Sebastian Goodman; Wei-Lun Chao; Radu Soricut (ICCV, 2023)

Re-Imagen: Retrieval-Augmented Text-to-Image Generator. - Wenhu Chen; Hexiang Hu; Chitwan Saharia; William W. Cohen (ICLR, 2023)

Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understanding. - Kenton Lee; Mandar Joshi; Iulia Raluca Turc; Hexiang Hu; Fangyu Liu 001; Julian Martin Eisenschlos; Urvashi Khandelwal; Peter Shaw 004; Ming-Wei Chang; Kristina Toutanova (ICML, 2023)

Subject-driven Text-to-Image Generation via Apprenticeship Learning. - Wenhu Chen; Hexiang Hu; Yandong Li; Nataniel Ruiz; Xuhui Jia; Ming-Wei Chang; William W. Cohen (NeurIPS, 2023)

From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces. - Peter Shaw 004; Mandar Joshi; James Cohan; Jonathan Berant; Panupong Pasupat; Hexiang Hu; Urvashi Khandelwal; Kenton Lee; Kristina Toutanova (NeurIPS, 2023)

PaLI-X: On Scaling up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CoRR, 2023)

Drinking From a Firehose: Continual Learning With Web-Scale Natural Language. - Hexiang Hu; Ozan Sener; Fei Sha; Vladlen Koltun (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

On Scaling Up a Multilingual Vision and Language Model. - Xi Chen 071; Josip Djolonga; Piotr Padlewski; Basil Mustafa; Soravit Changpinyo; Jialin Wu; Carlos Riquelme Ruiz; Sebastian Goodman; Xiao Wang 038; Yi Tay; Siamak Shakeri; Mostafa Dehghani 001; et al. (CVPR, 2024)

Instruct-Imagen: Image Generation with Multi-modal Instruction. - Hexiang Hu; Kelvin C. K. Chan; Yu-Chuan Su; Wenhu Chen; Yandong Li; Kihyuk Sohn; Yang Zhao; Xue Ben; Boqing Gong; William W. Cohen; Ming-Wei Chang; Xuhui Jia (CVPR, 2024)

UniIR: Training and Benchmarking Universal Multimodal Information Retrievers. - Cong Wei 001; Yang Chen; Haonan Chen; Hexiang Hu; Ge Zhang 009; Jie Fu 001; Alan Ritter; Wenhu Chen (ECCV (87), 2024)

MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions. - Kai Zhang 033; Yi Luan; Hexiang Hu; Kenton Lee; Siyuan Qiao; Wenhu Chen; Yu Su 001; Ming-Wei Chang (ICML, 2024)

Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (CoRR, 2024)

Imagen 3. - Jason Baldridge; Jakob Bauer; Mukul Bhutani; Nicole Brichtova; Andrew Bunner; Kelvin Chan; Yichang Chen; Sander Dieleman; Yuqing Du; Zach Eaton-Rosen; Hongliang Fei; Nando de Freitas; et al. (CoRR, 2024)

KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities. - Hsin-Ping Huang; Xinyi Wang; Yonatan Bitton; Hagai Taitelbaum; Gaurav Singh Tomar; Ming-Wei Chang; Xuhui Jia; Kelvin C. K. Chan; Hexiang Hu; Yu-Chuan Su; Ming-Hsuan Yang 001 (CoRR, 2024)

Scaling Inference Time Compute for Diffusion Models. - Nanye Ma; Shangyuan Tong; Haolin Jia; Hexiang Hu; Yu-Chuan Su; Mingda Zhang; Xuan Yang; Yandong Li; Tommi S. Jaakkola; Xuhui Jia; Saining Xie (CVPR, 2025)

OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities. - Lichang Chen; Hexiang Hu; Mingda Zhang; Yiwen Chen; Zifeng Wang; Yandong Li; Pranav Shyam; Tianyi Zhou 001; Heng Huang; Ming-Hsuan Yang 001; Boqing Gong (ICLR, 2025)

MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks. - Jiacheng Chen; Tianhao Liang; Sherman Siu; Zhengqing Wang; Kai Wang 068; Yubo Wang 019; Yuansheng Ni; Ziyan Jiang; Wang Zhu 001; Bohan Lyu 001; Dongfu Jiang; Xuan He; et al. (ICLR, 2025)

LOFT: Scalable and More Realistic Long-Context Evaluation. - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (NAACL (Findings), 2025)

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps. - Nanye Ma; Shangyuan Tong; Haolin Jia; Hexiang Hu; Yu-Chuan Su; Mingda Zhang; Xuan Yang; Yandong Li; Tommi S. Jaakkola; Xuhui Jia; Saining Xie (CoRR, 2025)