| 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 | 302* | 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 | 148 | 2019 |
| 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 | 99 | 2022 |
| Faithful Multimodal Explanation for Visual Question Answering J Wu, RJ Mooney Proceedings of the Second BlackboxNLP Workshop on Analyzing and Interpreting …, 2018 | 97 | 2018 |
| 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 | 80 | 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 | 77 | 2023 |
| Generating question relevant captions to aid visual question answering J Wu, Z Hu, RJ Mooney arXiv preprint arXiv:1906.00513, 2019 | 61* | 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 | 58* | 2018 |
| Improving vqa and its explanations\\by comparing competing explanations J Wu, L Chen, RJ Mooney arXiv preprint arXiv:2006.15631, 2020 | 23 | 2020 |
| 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 | 22 | 2023 |
| Action Recognition with Joint Attention on Multi-Level Deep Features J Wu, G Wang, W Yang, X Ji arXiv preprint arXiv:1607.02556, 2016 | 20 | 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 | 16 | 2021 |
| 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 | 12 | 2020 |
| Open X-Embodiment: Robotic learning datasets and RT-X models OXE Collaboration, A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, ... CoRR, 2023 | 10 | 2023 |
| Entity-focused dense passage retrieval for outside-knowledge visual question answering J Wu, RJ Mooney arXiv preprint arXiv:2210.10176, 2022 | 8 | 2022 |
| CausalLM is not optimal for in-context learning N Ding, T Levinboim, J Wu, S Goodman, R Soricut arXiv preprint arXiv:2308.06912, 2023 | 5 | 2023 |
| RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control, July 2023a A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ... URL http://arxiv. org/abs/2307.15818, 0 | 5 | |
| Higher Order Mutual Information Approximation for Feature Selection J Wu, S Gupta, C Bajaj arXiv preprint arXiv:1612.00554, 2016 | 4 | 2016 |
| 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 | 3 | 2023 |
| Reframing explanation as an interactive medium: The EQUAS (Explainable QUestion Answering System) project W Ferguson, D Batra, R Mooney, D Parikh, A Torralba, D Bau, D Diller, ... Applied AI Letters 2 (4), e60, 2021 | 3 | 2021 |
Raymond MooneyProfessor of Computer Science, University of Texas at AustinBestätigte E-Mail-Adresse bei cs.utexas.edu
