Deep Colorization by Variation. - Zineng Tang (CIKM, 2019)

Adaptive Aesthetic Photo Filter by Deep Learning. - Zineng Tang (ICVARS, 2019)

Dense-Caption Matching and Frame-Selection Gating for Temporal Localization in VideoQA. - Hyounghun Kim; Zineng Tang; Mohit Bansal (ACL, 2020)

Continuous Language Generative Flow. - Zineng Tang; Shiyue Zhang 001; Hyounghun Kim; Mohit Bansal (ACL/IJCNLP (1), 2021)

DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy Minimization. - Zineng Tang; Jie Lei 003; Mohit Bansal (NAACL-HLT, 2021)

VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer. - Zineng Tang; Jaemin Cho 001; Hao Tan 002; Mohit Bansal (NeurIPS, 2021)

TVLT: Textless Vision-Language Transformer. - Zineng Tang; Jaemin Cho 001; Yixin Nie; Mohit Bansal (NeurIPS, 2022)

Unifying Vision, Text, and Layout for Universal Document Processing. - Zineng Tang; Ziyi Yang; Guoxin Wang; Yuwei Fang; Yang Liu 124; Chenguang Zhu 001; Michael Zeng 001; Cha Zhang; Mohit Bansal (CVPR, 2023)

Any-to-Any Generation via Composable Diffusion. - Zineng Tang; Ziyi Yang; Chenguang Zhu 001; Michael Zeng 001; Mohit Bansal (NeurIPS, 2023)

Paxion: Patching Action Knowledge in Video-Language Foundation Models. - Zhenhailong Wang; Ansel Blume; Sha Li; Genglin Liu; Jaemin Cho 001; Zineng Tang; Mohit Bansal; Heng Ji 001 (NeurIPS, 2023)

PERCEIVER-VL: Efficient Vision-and-Language Modeling with Iterative Latent Attention. - Zineng Tang; Jaemin Cho 001; Jie Lei 003; Mohit Bansal (WACV, 2023)

CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation. - Zineng Tang; Ziyi Yang; Mahmoud Khademi; Yang Liu; Chenguang Zhu; Mohit Bansal (CVPR, 2024)

Grounding Language in Multi-Perspective Referential Communication. - Zineng Tang; Lingjun Mao; Alane Suhr (EMNLP, 2024)

AMONGAGENTS: Evaluating Large Language Models in the Interactive Text-Based Social Deduction Game. - Yizhou Chi; Lingjun Mao; Zineng Tang (CoRR, 2024)

Evaluating Model Perception of Color Illusions in Photorealistic Scenes. - Lingjun Mao; Zineng Tang; Alane Suhr (CVPR, 2025)

TULIP: Towards Unified Language-Image Pretraining. - Zineng Tang; Long Lian; Seun Eisape; Xudong Wang 007; Roei Herzig; Adam Yala; Alane Suhr; Trevor Darrell; David M. Chan (CoRR, 2025)

Images are Worth Variable Length of Representations. - Lingjun Mao; Rodolfo Corona; Xin Liang; Wenhao Yan; Zineng Tang (CoRR, 2025)