| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1318 | 2022 |
| On Measuring and Mitigating Biased Inferences of Word Embeddings S Dev, T Li, J Philips, V Srikumar AAAI 2020, 2019 | 191 | 2019 |
| Augmenting Neural Networks with First-order Logic T Li, V Srikumar Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 156 | 2019 |
| UNQOVERing stereotyping biases via underspecified questions T Li, T Khot, D Khashabi, A Sabharwal, V Srikumar EMNLP findings 2020, 2020 | 143 | 2020 |
| A Logic-Driven Framework for Consistency of Neural Models T Li, V Gupta, M Mehta, V Srikumar Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 99 | 2019 |
| Nlize: A perturbation-driven visual interrogation tool for analyzing and interpreting natural language inference models S Liu, Z Li, T Li, V Srikumar, V Pascucci, PT Bremer IEEE transactions on visualization and computer graphics 25 (1), 651-660, 2018 | 66 | 2018 |
| OSCaR: Orthogonal subspace correction and rectification of biases in word embeddings S Dev, T Li, JM Phillips, V Srikumar EMNLP 2021, 2020 | 58 | 2020 |
| Structured Tuning for Semantic Role Labeling T Li, Jawale, P Anand, M Palmer, V Srikumar Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 42 | 2020 |
| PYLON: A PyTorch Framework for Learning with Constraints K Ahmed, T Li, T Ton, Q Guo, KW Chang, P Kordjamshidi, V Srikumar, ... NeurIPS Demo, 2021 | 36 | 2021 |
| Visual interrogation of attention-based models for natural language inference and machine comprehension S Liu, T Li, Z Li, V Srikumar, V Pascucci, PT Bremer Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2018 | 36 | 2018 |
| On Data Augmentation for Extreme Multi-label Classification D Zhang, T Li, H Zhang, B Yin https://arxiv.org/abs/2009.10778, 2020 | 35 | 2020 |
| Prediction of Obstructive Lung Disease from Chest Radiographs via Deep Learning Trained on Pulmonary Function Data JD Schroeder, RB Lanfredi, T Li, J Chan, C Vachet, R Paine, V Srikumar, ... International Journal of Chronic Obstructive Pulmonary Disease, 2020 | 34 | 2020 |
| A Zero-Shot Language Agent for Computer Control with Structured Reflection T Li, G Li, Z Deng, B Wang, Y Li Findings of EMNLP 2023, 2023 | 17 | 2023 |
| LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing J Du, Y Wang, W Zhao, Z Deng, S Liu, R Lou, H Peng, P Narayanan, ... https://arxiv.org/abs/2406.16253, 2024 | 13 | 2024 |
| MUG: Interactive Multimodal Grounding on User Interfaces T Li, G Li, J Zheng, P Wang, Y Li https://arxiv.org/abs/2209.15099, 2022 | 9 | 2022 |
| Exploiting Sentence Similarities for Better Alignments T Li, V Srikumar Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016 | 9 | 2016 |
| Automatic entity state annotation using the VerbNet semantic parser G Kazeminejad, M Palmer, T Li, V Srikumar Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd …, 2021 | 8 | 2021 |
| Automatic Macro Mining from Interaction Traces at Scale F Huang, G Li, T Li, Y Li Proceedings of the CHI Conference on Human Factors in Computing Systems, 1-16, 2024 | 7 | 2024 |
| Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression Z Xu, A Gupta, T Li, O Bentham, V Srikumar https://arxiv.org/abs/2407.04965, 2024 | 4 | 2024 |
| Devil’s Advocate: Anticipatory Reflection for LLM Agents H Wang, T Li, Z Deng, D Roth, Y Li https://arxiv.org/abs/2405.16334, 2024 | 2 | 2024 |
Vivek SrikumarAssociate Professor, School of Computing, University of UtahZweryfikowany adres z cs.utah.edu