Papers with LLaMA 3-13B
Knowledge Augmentation Enhances Token Classification for Recipe Understanding (2026.eacl-long)
Copied to clipboard
| Challenge: | Using entity type-specific and knowledge-augmented token classification, we achieve state-of-the-art (SOTA) results on 5 out of 7 benchmark recipe datasets, significantly outperforming traditional token classification methods. |
| Approach: | They propose an entity type-specific and knowledge-augmented token classification framework to improve encoder models’ performance on recipe texts. |
| Outcome: | The proposed model outperforms traditional token classification methods on 5 out of 7 recipe datasets and is the largest annotated food-related dataset to date. |