Evaluating the factual consistency of abstractive text summarization W Kryściński, B McCann, C Xiong, R Socher arXiv preprint arXiv:1910.12840, 2019 | 781 | 2019 |
Summeval: Re-evaluating summarization evaluation AR Fabbri, W Kryściński, B McCann, C Xiong, R Socher, D Radev Transactions of the Association for Computational Linguistics 9, 391-409, 2021 | 722 | 2021 |
Neural text summarization: A critical evaluation W Kryściński, NS Keskar, B McCann, C Xiong, R Socher arXiv preprint arXiv:1908.08960, 2019 | 436 | 2019 |
Improving abstraction in text summarization W Kryściński, R Paulus, C Xiong, R Socher arXiv preprint arXiv:1808.07913, 2018 | 209 | 2018 |
Folio: Natural language reasoning with first-order logic S Han, H Schoelkopf, Y Zhao, Z Qi, M Riddell, W Zhou, J Coady, D Peng, ... arXiv preprint arXiv:2209.00840, 2022 | 166* | 2022 |
Ctrlsum: Towards generic controllable text summarization J He, W Kryściński, B McCann, N Rajani, C Xiong arXiv preprint arXiv:2012.04281, 2020 | 154 | 2020 |
Booksum: A collection of datasets for long-form narrative summarization W Kryściński, N Rajani, D Agarwal, C Xiong, D Radev arXiv preprint arXiv:2105.08209, 2021 | 134 | 2021 |
FeTaQA: Free-form table question answering L Nan, C Hsieh, Z Mao, XV Lin, N Verma, R Zhang, W Kryściński, ... Transactions of the Association for Computational Linguistics 10, 35-49, 2022 | 114* | 2022 |
Understanding factual errors in summarization: Errors, summarizers, datasets, error detectors L Tang, T Goyal, AR Fabbri, P Laban, J Xu, S Yavuz, W Kryściński, ... arXiv preprint arXiv:2205.12854, 2022 | 86 | 2022 |
Abstraction of text summarization R Paulus, W Kryscinski, C Xiong US Patent 10,909,157, 2021 | 74 | 2021 |
Long document summarization with top-down and bottom-up inference B Pang, E Nijkamp, W Kryściński, S Savarese, Y Zhou, C Xiong arXiv preprint arXiv:2203.07586, 2022 | 55 | 2022 |
Exploring neural models for query-focused summarization J Vig, AR Fabbri, W Kryściński, CS Wu, W Liu arXiv preprint arXiv:2112.07637, 2021 | 48 | 2021 |
Xgen-7b technical report E Nijkamp, T Xie, H Hayashi, B Pang, C Xia, C Xing, J Vig, S Yavuz, ... arXiv preprint arXiv:2309.03450, 2023 | 45* | 2023 |
SummEdits: Measuring LLM ability at factual reasoning through the lens of summarization P Laban, W Kryściński, D Agarwal, AR Fabbri, C Xiong, S Joty, CS Wu Proceedings of the 2023 conference on empirical methods in natural language …, 2023 | 43 | 2023 |
Llms as factual reasoners: Insights from existing benchmarks and beyond P Laban, W Kryściński, D Agarwal, AR Fabbri, C Xiong, S Joty, CS Wu arXiv preprint arXiv:2305.14540, 2023 | 34 | 2023 |
Improving the faithfulness of abstractive summarization via entity coverage control H Zhang, S Yavuz, W Kryscinski, K Hashimoto, Y Zhou arXiv preprint arXiv:2207.02263, 2022 | 34 | 2022 |
SummVis: Interactive visual analysis of models, data, and evaluation for text summarization J Vig, W Kryściński, K Goel, NF Rajani arXiv preprint arXiv:2104.07605, 2021 | 23 | 2021 |
HydraSum: Disentangling style features in text summarization with multi-decoder models T Goyal, N Rajani, W Liu, W Kryściński Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 22* | 2022 |
Socratic pretraining: Question-driven pretraining for controllable summarization A Pagnoni, AR Fabbri, W Kryściński, CS Wu arXiv preprint arXiv:2212.10449, 2022 | 17 | 2022 |
Evaluating the Factual Consistency of Abstractive Text Summarization W Kryscinski, B McCann US Patent App. 16/750,598, 2021 | 14 | 2021 |