| Beyond accuracy: Behavioral testing of NLP models with CheckList MT Ribeiro, T Wu, C Guestrin, S Singh Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 1165 | 2020 |
| Does the whole exceed its parts? the effect of ai explanations on complementary team performance G Bansal, T Wu, J Zhou, R Fok, B Nushi, E Kamar, MT Ribeiro, D Weld Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 669 | 2021 |
| Ai chains: Transparent and controllable human-ai interaction by chaining large language model prompts T Wu, M Terry, CJ Cai Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022 | 509 | 2022 |
| Tool learning with foundation models Y Qin, S Hu, Y Lin, W Chen, N Ding, G Cui, Z Zeng, Y Huang, C Xiao, ... ACM Computing Surveys, 2024 | 321 | 2024 |
| Polyjuice: Generating counterfactuals for explaining, evaluating, and improving models T Wu, MT Ribeiro, J Heer, DS Weld Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 295* | 2021 |
| Promptchainer: Chaining large language model prompts through visual programming T Wu, E Jiang, A Donsbach, J Gray, A Molina, M Terry, CJ Cai CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1-10, 2022 | 216 | 2022 |
| No explainability without accountability: An empirical study of explanations and feedback in interactive ml A Smith-Renner, R Fan, M Birchfield, T Wu, J Boyd-Graber, DS Weld, ... Proceedings of the 2020 chi conference on human factors in computing systems …, 2020 | 163 | 2020 |
| Errudite: Scalable, Reproducible, and Testable Error Analysis T Wu, MT Ribeiro, J Heer, DS Weld Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 160 | 2019 |
| Storybuddy: A human-ai collaborative chatbot for parent-child interactive storytelling with flexible parental involvement Z Zhang, Y Xu, Y Wang, B Yao, D Ritchie, T Wu, M Yu, D Wang, TJJ Li Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems …, 2022 | 133 | 2022 |
| Fantastic Questions and Where to Find Them: FairytaleQA--An Authentic Dataset for Narrative Comprehension Y Xu, D Wang, M Yu, D Ritchie, B Yao, T Wu, Z Zhang, TJJ Li, N Bradford, ... Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 97 | 2022 |
| Tailor: Generating and perturbing text with semantic controls A Ross, T Wu, H Peng, ME Peters, M Gardner Proceedings of the 60th Annual Meeting of the Association for Computational …, 2021 | 81 | 2021 |
| Bridging the gap: A survey on integrating (human) feedback for natural language generation P Fernandes, A Madaan, E Liu, A Farinhas, PH Martins, A Bertsch, ... Transactions of the Association of Computational Linguistics, 2023 | 78 | 2023 |
| Nl-augmenter: A framework for task-sensitive natural language augmentation KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ... Northern European Journal of Language Technology 9 (1), 2021 | 78 | 2021 |
| A large-scale audit of dataset licensing and attribution in AI S Longpre, R Mahari, A Chen, N Obeng-Marnu, D Sileo, W Brannon, ... Nature Machine Intelligence 6 (8), 975-987, 2024 | 66* | 2024 |
| Do llms exhibit human-like response biases? a case study in survey design L Tjuatja, V Chen, T Wu, A Talwalkwar, G Neubig Transactions of the Association for Computational Linguistics 12, 1011-1026, 2024 | 65* | 2024 |
| Towards Natural Language-Based Visualization Authoring Y Wang, Z Hou, L Shen, T Wu, J Wang, H Huang, H Zhang, D Zhang IEEE Transactions on Visualization and Computer Graphics 29 (1), 1222-1232, 2022 | 60 | 2022 |
| Large language models enable few-shot clustering V Viswanathan, K Gashteovski, K Gashteovski, C Lawrence, T Wu, ... Transactions of the Association for Computational Linguistics 12, 321-333, 2024 | 57 | 2024 |
| It is AI's Turn to Ask Humans a Question: Question-Answer Pair Generation for Children's Story Books B Yao, D Wang, T Wu, Z Zhang, TJJ Li, M Yu, Y Xu Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 56* | 2022 |
| Local decision pitfalls in interactive machine learning: An investigation into feature selection in sentiment analysis T Wu, DS Weld, J Heer ACM Transactions on Computer-Human Interaction (TOCHI) 26 (4), 1-27, 2019 | 56 | 2019 |
| NameClarifier: A Visual Analytics System for Author Name Disambiguation Q Shen, T Wu, H Yang, Y Wu, H Qu, W Cui IEEE Transactions on Visualization & Computer Graphics, 141-150, 2017 | 53 | 2017 |
Marco Tulio RibeiroGoogle DeepMindVerificeret mail på cs.washington.edu
