Papers by John Muchovej
Analyzing Sentence Fusion in Abstractive Summarization (D19-54)
Copied to clipboard
Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu
| Challenge: | Abstractive summarization systems struggle to combine information from multiple sources, resulting in poor grammar and incorrect facts. |
| Approach: | They analyze the outputs of five abstractive summarization systems and examine their grammatical accuracy and faithfulness. |
| Outcome: | The proposed summarization systems are able to combine information from multiple sources, but they often fail to remain faithful to the original document. |
Understanding Points of Correspondence between Sentences for Abstractive Summarization (2020.acl-srw)
Copied to clipboard
| Challenge: | Using points of correspondence, fusion systems are difficult for abstractive summarizers because of their complexity. |
| Approach: | They propose to model points of correspondence between disparate sentences by combining documents, source and fusion sentences, and human annotations of points of correspondance between sentences. |
| Outcome: | The proposed model bridges the gap between coreference resolution and summarization by using human annotations of points of correspondence between sentences. |