| Rt-2: Vision-language-action models transfer web knowledge to robotic control B Zitkovich, T Yu, S Xu, P Xu, T Xiao, F Xia, J Wu, P Wohlhart, S Welker, ... Conference on Robot Learning, 2165-2183, 2023 | 615* | 2023 |
| Open x-embodiment: Robotic learning datasets and rt-x models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 209 | 2023 |
| Self-Critical Reasoning for Robust Visual Question Answering J Wu, RJ Mooney Proceedings of the Thirty-third Conference on Advances in Neural Information …, 2019 | 163 | 2019 |
| Pali-x: On scaling up a multilingual vision and language model X Chen, J Djolonga, P Padlewski, B Mustafa, S Changpinyo, J Wu, ... arXiv preprint arXiv:2305.18565, 2023 | 124 | 2023 |
| Multi-modal answer validation for knowledge-based vqa J Wu, J Lu, A Sabharwal, R Mottaghi Proceedings of the AAAI conference on artificial intelligence 36 (3), 2712-2721, 2022 | 124 | 2022 |
| Faithful Multimodal Explanation for Visual Question Answering J Wu, RJ Mooney Proceedings of the Second BlackboxNLP Workshop on Analyzing and Interpreting …, 2018 | 106 | 2018 |
| Generating question relevant captions to aid visual question answering J Wu, Z Hu, RJ Mooney arXiv preprint arXiv:1906.00513, 2019 | 64* | 2019 |
| Dynamic filtering with large sampling field for convnets J Wu, D Li, Y Yang, C Bajaj, X Ji Proceedings of the European Conference on Computer Vision (ECCV), 185-200, 2018 | 60* | 2018 |
| Pali-3 vision language models: Smaller, faster, stronger X Chen, X Wang, L Beyer, A Kolesnikov, J Wu, P Voigtlaender, B Mustafa, ... arXiv preprint arXiv:2310.09199, 2023 | 50 | 2023 |
| Open X-Embodiment: Robotic learning datasets and RT-X models OXE Collaboration, A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, ... arXiv preprint arXiv:2310.08864, 2023 | 35 | 2023 |
| Improving vqa and its explanations\\by comparing competing explanations J Wu, L Chen, RJ Mooney arXiv preprint arXiv:2006.15631, 2020 | 24 | 2020 |
| Action Recognition with Joint Attention on Multi-Level Deep Features J Wu, G Wang, W Yang, X Ji arXiv preprint arXiv:1607.02556, 2016 | 21 | 2016 |
| Visual question answering based on local-scene-aware referring expression generation JJ Kim, DG Lee, J Wu, HG Jung, SW Lee Neural Networks 139, 158-167, 2021 | 19 | 2021 |
| Geomverse: A systematic evaluation of large models for geometric reasoning M Kazemi, H Alvari, A Anand, J Wu, X Chen, R Soricut arXiv preprint arXiv:2312.12241, 2023 | 17 | 2023 |
| CoNAN: A complementary neighboring-based attention network for referring expression generation J Kim, H Ko, J Wu Proceedings of the 28th International Conference on Computational …, 2020 | 14 | 2020 |
| CausalLM is not optimal for in-context learning N Ding, T Levinboim, J Wu, S Goodman, R Soricut arXiv preprint arXiv:2308.06912, 2023 | 12 | 2023 |
| Entity-focused dense passage retrieval for outside-knowledge visual question answering J Wu, RJ Mooney arXiv preprint arXiv:2210.10176, 2022 | 11 | 2022 |
| Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 A O’Neill, A Rehman, A Maddukuri, A Gupta, A Padalkar, A Lee, A Pooley, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, 2024 | 9 | 2024 |
| Non-intrusive adaptation: Input-centric parameter-efficient fine-tuning for versatile multimodal modeling Y Wang, J Wu, T Dabral, J Zhang, G Brown, CT Lu, F Liu, Y Liang, B Pang, ... arXiv preprint arXiv:2310.12100, 2023 | 8 | 2023 |
| Distilling vision-language models on millions of videos Y Zhao, L Zhao, X Zhou, J Wu, CT Chu, H Miao, F Schroff, H Adam, T Liu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 7 | 2024 |
Raymond MooneyProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
