| Decembert: Learning from noisy instructional videos via dense captions and entropy minimization Z Tang, J Lei, M Bansal Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 54 | 2021 |
| Dense-caption matching and frame-selection gating for temporal localization in VideoQA H Kim, Z Tang, M Bansal arXiv preprint arXiv:2005.06409, 2020 | 33 | 2020 |
| Vidlankd: Improving language understanding via video-distilled knowledge transfer Z Tang, J Cho, H Tan, M Bansal Advances in Neural Information Processing Systems 34, 24468-24481, 2021 | 21 | 2021 |
| Any-to-Any Generation via Composable Diffusion Z Tang, Z Yang, C Zhu, M Zeng, M Bansal arXiv preprint arXiv:2305.11846, 2023 | 19 | 2023 |
| Unifying vision, text, and layout for universal document processing Z Tang, Z Yang, G Wang, Y Fang, Y Liu, C Zhu, M Zeng, C Zhang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 19 | 2022 |
| TVLT: Textless vision-language transformer Z Tang, J Cho, Y Nie, M Bansal Advances in Neural Information Processing Systems 35, 9617-9632, 2022 | 16 | 2022 |
| Paxion: Patching Action Knowledge in Video-Language Foundation Models Z Wang, A Blume, S Li, G Liu, J Cho, Z Tang, M Bansal, H Ji arXiv preprint arXiv:2305.10683, 2023 | 6 | 2023 |
| Perceiver-vl: Efficient vision-and-language modeling with iterative latent attention Z Tang, J Cho, J Lei, M Bansal Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 4 | 2023 |
| Deep colorization by variation Z Tang Proceedings of the 28th ACM International Conference on Information and …, 2019 | 2 | 2019 |
| Continuous language generative flow Z Tang, S Zhang, H Kim, M Bansal Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 1 | 2021 |
| CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation Z Tang, Z Yang, M Khademi, Y Liu, C Zhu, M Bansal arXiv preprint arXiv:2311.18775, 2023 | | 2023 |
| Supplementary Materials for TVLT: Textless Vision-Language Transformer Z Tang, J Cho, Y Nie, M Bansal | | |
| Supplementary Material for PERCEIVER-VL: Efficient Vision-and-Language Modeling with Iterative Latent Attention Z Tang, J Cho, JLM Bansal | | |
Mohit BansalParker Professor, Computer Science, UNC Chapel HillVerified email at cs.unc.edu
