Papers by Ting-Chih Chen
M3D: MultiModal MultiDocument Fine-Grained Inconsistency Detection (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for fact-checking claim are limited by ambiguous information and lack sample-level predictions. |
| Approach: | They propose a method that predicts the logical relationship of each aspect of a claim from a set of multimodal documents. |
| Outcome: | The proposed method outperforms existing models on two benchmarks while providing finer-grained predictions, explanations, and evidence. |
MetaSumPerceiver: Multimodal Multi-Document Evidence Summarization for Fact-Checking (2024.acl-long)
Copied to clipboard
| Challenge: | Fact-checking claims on social media platforms poses a significant challenge due to the large volume of new claims constantly being posted without sufficient methods for verification. |
| Approach: | They propose a model that generates claim-specific summaries from multimodal multi-document datasets using a perceiver-based model that is able to handle inputs from multiple modalities of arbitrary lengths. |
| Outcome: | The proposed model outperforms the SOTA approach by 4.6% in the claim verification task on the MOCHEG dataset and shows strong performance on the new multi-document claims dataset. |