| What does bert look at? an analysis of bert's attention K Clark, U Khandelwal, O Levy, CD Manning Proceedings of the Second BlackboxNLP Workshop on Analyzing and Interpreting …, 2019 | 1585 | 2019 |
| Personalized entity recommendation: A heterogeneous information network approach X Yu, X Ren, Y Sun, Q Gu, B Sturt, U Khandelwal, B Norick, J Han Proceedings of the 7th ACM international conference on Web search and data …, 2014 | 856 | 2014 |
| Generalization through memorization: Nearest neighbor language models U Khandelwal, O Levy, D Jurafsky, L Zettlemoyer, M Lewis International Conference on Learning Representations (ICLR), 2020 | 595 | 2020 |
| Sharp nearby, fuzzy far away: How neural language models use context U Khandelwal, H He, P Qi, D Jurafsky Proceedings to the 56th Annual Meeting of the Association for Computational …, 2018 | 361 | 2018 |
| Emergent linguistic structure in artificial neural networks trained by self-supervision CD Manning, K Clark, J Hewitt, U Khandelwal, O Levy Proceedings of the National Academy of Sciences 117 (48), 30046-30054, 2020 | 314 | 2020 |
| Nearest neighbor machine translation U Khandelwal, A Fan, D Jurafsky, L Zettlemoyer, M Lewis International Conference on Learning Representations (ICLR), 2021 | 247 | 2021 |
| Recommendation in heterogeneous information networks with implicit user feedback X Yu, X Ren, Y Sun, B Sturt, U Khandelwal, Q Gu, B Norick, J Han Proceedings of the 7th ACM conference on Recommender systems, 347-350, 2013 | 230 | 2013 |
| Bam! born-again multi-task networks for natural language understanding K Clark, MT Luong, U Khandelwal, CD Manning, QV Le Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 211 | 2019 |
| Cluscite: Effective citation recommendation by information network-based clustering X Ren, J Liu, X Yu, U Khandelwal, Q Gu, L Wang, J Han Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 161 | 2014 |
| Pix2struct: Screenshot parsing as pretraining for visual language understanding K Lee, M Joshi, IR Turc, H Hu, F Liu, JM Eisenschlos, U Khandelwal, ... International Conference on Machine Learning, 18893-18912, 2023 | 117 | 2023 |
| With little power comes great responsibility D Card, P Henderson, U Khandelwal, R Jia, K Mahowald, D Jurafsky Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 101 | 2020 |
| Sample efficient text summarization using a single pre-trained transformer U Khandelwal, K Clark, D Jurafsky, L Kaiser arXiv preprint arXiv:1905.08836, 2019 | 95 | 2019 |
| From pixels to ui actions: Learning to follow instructions via graphical user interfaces P Shaw, M Joshi, J Cohan, J Berant, P Pasupat, H Hu, U Khandelwal, ... Advances in Neural Information Processing Systems 36, 2024 | 25 | 2024 |
| Open-domain visual entity recognition: Towards recognizing millions of wikipedia entities H Hu, Y Luan, Y Chen, U Khandelwal, M Joshi, K Lee, K Toutanova, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 18 | 2023 |
| Neural text summarization U Khandelwal, P Qi, D Jurafsky Stanford University, Stanford, CA, USA 92, 4701, 2016 | 5 | 2016 |
| Few-Shot Recalibration of Language Models XL Li, U Khandelwal, K Guu arXiv preprint arXiv:2403.18286, 2024 | | 2024 |
| Calibrated on Average, but not Within Each Slice: Few-shot Calibration for All Slices of a Distribution XL Li, U Khandelwal, K Guu | | 2023 |
| Open-domain Visual Entity Linking H Hu, Y Luan, U Khandelwal, M Joshi, K Lee, K Toutanova, MW Chang | | 2022 |
| Improving Neural Language Models with Black-Box Analysis and Generalization Through Memorization U Khandelwal Stanford University, 2021 | | 2021 |
| Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation A Bosselut, A Celikyilmaz, M Ghazvininejad, S Iyer, U Khandelwal, ... Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural …, 2019 | | 2019 |
