Papers by Sarah Kwan
Evaluating the Factual Consistency of Large Language Models Through News Summarization (2023.findings-acl)
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| Challenge: | Existing LLMs generally assign a higher score to factually consistent summaries than to factualally inconsistent summary. |
| Approach: | They propose a benchmark to measure whether large language models prefer factually consistent continuations of inputs. |
| Outcome: | The proposed benchmark compares the scores an LLM assigns to a factually consistent versus a inconsistent summary for an input news article. |