David Wan
Cited by
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FactPEGASUS: Factuality-aware pre-training and fine-tuning for abstractive summarization
D Wan, M Bansal
arXiv preprint arXiv:2205.07830, 2022
Extractive is not faithful: An investigation of broad unfaithfulness problems in extractive summarization
S Zhang, D Wan, M Bansal
arXiv preprint arXiv:2209.03549, 2022
Faithfulness-aware decoding strategies for abstractive summarization
D Wan, M Liu, K McKeown, M Dreyer, M Bansal
arXiv preprint arXiv:2303.03278, 2023
Incorporating terminology constraints in automatic post-editing
D Wan, C Kedzie, F Ladhak, M Carpuat, K McKeown
arXiv preprint arXiv:2010.09608, 2020
Evaluating and Improving Factuality in Multimodal Abstractive Summarization
D Wan, M Bansal
arXiv preprint arXiv:2211.02580, 2022
Constrained Regeneration for Cross-Lingual Query-Focused Extractive Summarization
E Turcan, D Wan, F Ladhak, P Galuščáková, S Sen, S Tchistiakova, W Xu, ...
Proceedings of the 29th International Conference on Computational …, 2022
Segmenting subtitles for correcting asr segmentation errors
D Wan, C Kedzie, F Ladhak, E Turcan, P Galuščáková, E Zotkina, Z Jiang, ...
arXiv preprint arXiv:2104.07868, 2021
Subtitles to Segmentation: Improving Low-Resource Speech-to-Text Translation Pipelines
D Wan, ZP Jiang, C Kedzie, E Turcan, P Bell, K McKeown
Proceedings of the workshop on Cross-Language Search and Summarization of …, 2020
HistAlign: Improving Context Dependency in Language Generation by Aligning with History
D Wan, S Zhang, M Bansal
arXiv preprint arXiv:2305.04782, 2023
System for Cross-Language Information Processing, Translation and Summarization (SCRIPTS)
K McKeown, J Hirschberg, S Muresan, R Eskander, F Ladhak, ...
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