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Wojciech Kryściński
Wojciech Kryściński
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Title
Cited by
Cited by
Year
Evaluating the factual consistency of abstractive text summarization
W Kryściński, B McCann, C Xiong, R Socher
arXiv preprint arXiv:1910.12840, 2019
6592019
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
5722021
Neural text summarization: A critical evaluation
W Kryściński, NS Keskar, B McCann, C Xiong, R Socher
arXiv preprint arXiv:1908.08960, 2019
3972019
Improving abstraction in text summarization
W Kryściński, R Paulus, C Xiong, R Socher
arXiv preprint arXiv:1808.07913, 2018
1882018
Ctrlsum: Towards generic controllable text summarization
J He, W Kryściński, B McCann, N Rajani, C Xiong
arXiv preprint arXiv:2012.04281, 2020
1322020
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
1002021
Folio: Natural language reasoning with first-order logic
S Han, H Schoelkopf, Y Zhao, Z Qi, M Riddell, L Benson, L Sun, E Zubova, ...
arXiv preprint arXiv:2209.00840, 2022
98*2022
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
73*2022
Abstraction of text summarization
R Paulus, W Kryscinski, C Xiong
US Patent 10,909,157, 2021
652021
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
612022
Exploring neural models for query-focused summarization
J Vig, AR Fabbri, W Kryściński, CS Wu, W Liu
arXiv preprint arXiv:2112.07637, 2021
412021
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
372022
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
30*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
262022
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
232023
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
202021
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
17*2022
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
142023
Socratic pretraining: Question-driven pretraining for controllable summarization
A Pagnoni, AR Fabbri, W Kryściński, CS Wu
arXiv preprint arXiv:2212.10449, 2022
122022
What's New? Summarizing Contributions in Scientific Literature
H Hayashi, W Kryściński, B McCann, N Rajani, C Xiong
arXiv preprint arXiv:2011.03161, 2020
102020
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