| Content planning for neural story generation with aristotelian rescoring S Goldfarb-Tarrant, T Chakrabarty, R Weischedel, N Peng Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 107 | 2020 |
| AMPERSAND: Argument Mining for PERSuAsive oNline Discussions T Chakrabarty, C Hidey, S Muresan, K Mckeown, A Hwang EMNLP 2019 , 2933–2943, 2020 | 105 | 2020 |
| COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic A Saakyan, T Chakrabarty, S Muresan Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 86 | 2021 |
| : Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge T Chakrabarty, D Ghosh, S Muresan, N Peng ACL 2020, 7976–7986, 2020 | 69 | 2020 |
| IMHO Fine-Tuning Improves Claim Detection T Chakrabarty, C Hidey, K McKeown NAACL 2019, 558–563, 2019 | 64 | 2019 |
| Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation T Chakrabarty, S Muresan, N Peng Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 61 | 2020 |
| Fine-tuned Language Models are Continual Learners T Scialom, T Chakrabarty, S Muresan EMNLP 2022, 2022 | 59* | 2022 |
| MERMAID: Metaphor Generation with Symbolism and Discriminative Decoding T Chakrabarty, X Zhang, S Muresan, N Peng 2021 Annual Conference of the North American Chapter of the Association for …, 2021 | 51 | 2021 |
| DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking C Hidey, T Chakrabarty, T Alhindi, S Varia, K Krstovski, M Diab, ... ACL 2020,8593–8606, 2020 | 46 | 2020 |
| FLUTE: Figurative Language Understanding through Textual Explanations T Chakrabarty, A Saakyan, D Ghosh, S Muresan EMNLP 2022, 2022 | 41* | 2022 |
| It’s not Rocket Science: Interpreting Figurative Language in Narratives T Chakrabarty, Y Choi, V Shwartz Transactions of the Association for Computational Linguistics 10, 589-606, 2022 | 41 | 2022 |
| Help me write a poem: Instruction Tuning as a Vehicle for Collaborative Poetry Writing T Chakrabarty, V Padmakumar, H He EMNLP 2022, 2022 | 40 | 2022 |
| Pay “Attention” to your Context when Classifying Abusive Language T Chakrabarty, K Gupta, S Muresan Proceedings of the Third Workshop on Abusive Language Online, 70-79, 2019 | 40 | 2019 |
| Metaphor Generation with Conceptual Mappings K Stowe, T Chakrabarty, N Peng, S Muresan, I Gurevych Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 33 | 2021 |
| Figurative Language in Recognizing Textual Entailment T Chakrabarty, D Ghosh, A Poliak, S Muresan Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 27 | 2021 |
| Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification. T Chakrabarty, T Alhindi, S Muresan Proceedings of the First Workshop on Fact Extraction and VERification (FEVER …, 2018 | 25 | 2018 |
| Discourse relation prediction: Revisiting word pairs with convolutional networks S Varia, C Hidey, T Chakrabarty Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue …, 2019 | 21 | 2019 |
| NormSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Fly YR Fung, T Chakraborty, H Guo, O Rambow, S Muresan, H Ji arXiv preprint arXiv:2210.08604, 2022 | 20 | 2022 |
| MFRED, 10 second interval real and reactive power for groups of 390 US apartments of varying size and vintage CJ Meinrenken, N Rauschkolb, S Abrol, T Chakrabarty, VC Decalf, ... Scientific Data 7 (1), 375, 2020 | 20 | 2020 |
| Art or Artifice? Large Language Models and the False Promise of Creativity T Chakrabarty, P Laban, D Agarwal, S Muresan, CS Wu arXiv preprint arXiv:2309.14556, 2023 | 17 | 2023 |
Smaranda MuresanColumbia UnviersityVerified email at ccls.columbia.edu
