Papers by Xingyun Wang
Exploring the Factual Consistency in Dialogue Comprehension of Large Language Models (2024.naacl-long)
Copied to clipboard
| Challenge: | LLMs generate responses following user's instructions, which requires high dialogue comprehension ability. |
| Approach: | They propose to evaluate LLMs' dialogue comprehension ability using a dialogue summarization task to derive factual questions from the generated summaries and use them as a more flexible measurement of dialogue comprehension. |
| Outcome: | The proposed model reduces the error rate by 11% on the dialogue summarization task. |