Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics (2021.naacl-main)
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| Challenge: | Modern summarization models generate fluent but often factually unreliable outputs. |
| Approach: | They propose to use human annotations to identify different categories of factual errors and benchmark factuality metrics to improve summarization evaluation. |
| Outcome: | The proposed method identifies the proportion of different categories of factual errors and benchmarks their human judgements as well as their specific strengths and weaknesses. |
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Subhajit Chaudhury, Sarathkrishna Swaminathan, Chulaka Gunasekara, Maxwell Crouse, Srinivas Ravishankar, Daiki Kimura, Keerthiram Murugesan, Ramón Fernandez Astudillo, Tahira Naseem, Pavan Kapanipathi, Alexander Gray
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