| Part-of-speech tagging for twitter: Annotation, features, and experiments K Gimpel, N Schneider, B O’connor, D Das, DP Mills, J Eisenstein, ... Proceedings of the 49th annual meeting of the Association for Computational …, 2011 | 1346 | 2011 |
| A Discriminative Graph-Based Parser for the Abstract Meaning Representation J Flanigan, S Thomson, J Carbonell, C Dyer, NA Smith Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014 | 410 | 2014 |
| Toward abstractive summarization using semantic representations F Liu, J Flanigan, S Thomson, N Sadeh, NA Smith arXiv preprint arXiv:1805.10399, 2018 | 362 | 2018 |
| Generation from abstract meaning representation using tree transducers J Flanigan, C Dyer, NA Smith, JG Carbonell Proceedings of the 2016 conference of the north american chapter of the …, 2016 | 149 | 2016 |
| The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures S Mysore, Z Jensen, E Kim, K Huang, HS Chang, E Strubell, J Flanigan, ... arXiv preprint arXiv:1905.06939, 2019 | 129 | 2019 |
| Task contamination: Language models may not be few-shot anymore C Li, J Flanigan Proceedings of the AAAI Conference on Artificial Intelligence 38 (16), 18471 …, 2024 | 81 | 2024 |
| Part-of-speech tagging for twitter: Annotation, features K Gimpel, N Schneider, B O’Connor, D Das, D Mills, J Eisenstein, ... and experiments. Technical report, Carnegie-Mellon Univ Pittsburgh Pa School …, 2010 | 74 | 2010 |
| CMU at SemEval-2016 task 8: Graph-based AMR parsing with infinite ramp loss J Flanigan, C Dyer, NA Smith, JG Carbonell Proceedings of the 10th International Workshop on Semantic Evaluation …, 2016 | 68 | 2016 |
| Diverse retrieval-augmented in-context learning for dialogue state tracking B King, J Flanigan arXiv preprint arXiv:2307.01453, 2023 | 21 | 2023 |
| Athena: Constructing dialogues dynamically with discourse constraints V Harrison, J Juraska, W Cui, L Reed, KK Bowden, J Wu, B Schwarzmann, ... arXiv preprint arXiv:2011.10683, 2020 | 18 | 2020 |
| Large language model unlearning via embedding-corrupted prompts C Liu, Y Wang, J Flanigan, Y Liu Advances in Neural Information Processing Systems 37, 118198-118266, 2025 | 17 | 2025 |
| Large-scale discriminative training for statistical machine translation using held-out line search J Flanigan, C Dyer, JG Carbonell Proceedings of the 2013 Conference of the North American Chapter of the …, 2013 | 17 | 2013 |
| Improving neural machine translation with the Abstract Meaning Representation by combining graph and sequence transformers C Li, J Flanigan Association for Computational Linguistics, 2022 | 16 | 2022 |
| CMU: Arc-factored, discriminative semantic dependency parsing S Thomson, B O’Connor, J Flanigan, D Bamman, J Dodge, ... Proceedings of the 8th International Workshop on Semantic Evaluation …, 2014 | 13 | 2014 |
| DocAMR: Multi-sentence AMR representation and evaluation T Naseem, A Blodgett, S Kumaravel, T O'Gorman, YS Lee, J Flanigan, ... arXiv preprint arXiv:2112.08513, 2021 | 9 | 2021 |
| Parsing and Generation for the Abstract Meaning Representation J Flanigan Carnegie Mellon University, Pittsburgh, 2018 | 7 | 2018 |
| The logic of amr: Practical, unified, graph-based sentence semantics for nlp N Schneider, J Flanigan, T O'Gorman NAACL HLT 2015, The 2015 Conference of the North American Chapter of the …, 2015 | 7 | 2015 |
| From learning optimization to learner flourishing: Reimagining AI in Education at the Institute for Student‐AI Teaming (iSAT) SK D'Mello, Q Biddy, T Breideband, J Bush, M Chang, A Cortez, ... AI Magazine 45 (1), 61-68, 2024 | 6 | 2024 |
| Dependency Dialogue Acts--Annotation Scheme and Case Study JZ Cai, B King, M Perkoff, S Dudy, J Cao, M Grace, N Wojarnik, A Ganesh, ... arXiv preprint arXiv:2302.12944, 2023 | 5 | 2023 |
| Meaning representations for natural languages: Design, models and applications J Flanigan, I Jindal, Y Li, T O’Gorman, M Palmer, N Xue Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 4 | 2022 |
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligencePatvirtintas el. paštas cs.washington.edu
