Papers by Lavisha Sharma
Mask-to-Correct+: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction (2026.acl-long)
Copied to clipboard
| Challenge: | Existing methods for fact correction ignore semantic faithfulness in their process. |
| Approach: | They propose a supervised learning approach that uses a diversity-aware masking approach to identify erroneous spans of claims and evaluate the faithfulness of corrections using retrieved evidence. |
| Outcome: | The proposed framework outperforms baseline frameworks on social media datasets, achieving up to 14% improvement in SARI scores, without using gold evidence. |