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 | 869 | 2022 |
Improving and simplifying pattern exploiting training D Tam, RR Menon, M Bansal, S Srivastava, C Raffel arXiv preprint arXiv:2103.11955, 2021 | 138 | 2021 |
Identifying metaphorical word use with tree kernels D Hovy, S Srivastava, SK Jauhar, M Sachan, K Goyal, H Li, W Sanders, ... Proceedings of the First Workshop on Metaphor in NLP, 52-57, 2013 | 107 | 2013 |
Joint concept learning and semantic parsing from natural language explanations S Srivastava, I Labutov, T Mitchell Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 98 | 2017 |
PRover: Proof generation for interpretable reasoning over rules S Saha, S Ghosh, S Srivastava, M Bansal arXiv preprint arXiv:2010.02830, 2020 | 78 | 2020 |
Zero-shot learning of classifiers from natural language quantification S Srivastava, I Labutov, T Mitchell Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 71 | 2018 |
Inferring interpersonal relations in narrative summaries S Srivastava, S Chaturvedi, T Mitchell Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 67 | 2016 |
Modeling evolving relationships between characters in literary novels S Chaturvedi, S Srivastava, H Daume III, C Dyer Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 53 | 2016 |
A walk-based semantically enriched tree kernel over distributed word representations S Srivastava, D Hovy, E Hovy Proceedings of the 2013 Conference on Empirical Methods in Natural Language …, 2013 | 39 | 2013 |
Spatial compactness meets topical consistency: Jointly modeling links and content for community detection M Sachan, A Dubey, S Srivastava, EP Xing, E Hovy Proceedings of the 7th ACM international conference on Web search and data …, 2014 | 29 | 2014 |
Identifying and manipulating the personality traits of language models G Caron, S Srivastava arXiv preprint arXiv:2212.10276, 2022 | 28 | 2022 |
A structured distributional semantic model for event co-reference K Goyal, SK Jauhar, H Li, M Sachan, S Srivastava, E Hovy Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013 | 26 | 2013 |
Where have i heard this story before? identifying narrative similarity in movie remakes S Chaturvedi, S Srivastava, D Roth Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 20 | 2018 |
LIA: A natural language programmable personal assistant I Labutov, S Srivastava, T Mitchell Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 16 | 2018 |
Adversarial scrubbing of demographic information for text classification SBR Chowdhury, S Ghosh, Y Li, JB Oliva, S Srivastava, S Chaturvedi arXiv preprint arXiv:2109.08613, 2021 | 14 | 2021 |
An agent for learning new natural language commands A Azaria, S Srivastava, J Krishnamurthy, I Labutov, TM Mitchell Autonomous Agents and Multi-Agent Systems 34 (1), 6, 2020 | 14 | 2020 |
Predicting difficulty and discrimination of natural language questions M Byrd, S Srivastava Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 11 | 2022 |
Parsing Natural Language Conversations using Contextual Cues. S Srivastava, A Azaria, TM Mitchell IJCAI, 4089-4095, 2017 | 11 | 2017 |
How helpful is inverse reinforcement learning for table-to-text generation? S Ghosh, Z Qi, S Chaturvedi, S Srivastava Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 10 | 2021 |
ePiC: Employing proverbs in context as a benchmark for abstract language understanding S Ghosh, S Srivastava arXiv preprint arXiv:2109.06838, 2021 | 9 | 2021 |