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Zineng Tang
Zineng Tang
UC Berkeley
E-mailová adresa ověřena na: cs.unc.edu - Domovská stránka
Název
Citace
Citace
Rok
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
582021
Any-to-any generation via composable diffusion
Z Tang, Z Yang, C Zhu, M Zeng, M Bansal
Advances in Neural Information Processing Systems 36, 2024
512024
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
472022
Dense-caption matching and frame-selection gating for temporal localization in VideoQA
H Kim, Z Tang, M Bansal
arXiv preprint arXiv:2005.06409, 2020
362020
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
252021
TVLT: Textless vision-language transformer
Z Tang, J Cho, Y Nie, M Bansal
Advances in Neural Information Processing Systems 35, 9617-9632, 2022
202022
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
Advances in Neural Information Processing Systems 36, 2024
82024
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
62023
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
62023
Continuous language generative flow
Z Tang, S Zhang, H Kim, M Bansal
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
22021
Deep colorization by variation
Z Tang
Proceedings of the 28th ACM International Conference on Information and …, 2019
22019
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
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Články 1–13