Papers by Dongwon Choi
MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories (2021.naacl-main)
Copied to clipboard
| Challenge: | Existing studies have developed computational models to recognize metaphorical words in sentences. |
| Approach: | They propose a model that leverages contextualized word representation and linguistic metaphor identification theories to detect whether the target word is metaphorical. |
| Outcome: | The proposed model outperforms baseline models on four benchmark datasets . it leverages contextualized word representation and linguistic metaphor identification theories to detect whether the target word is metaphorical. |
Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing approaches to document retrieval are coarse and efficient, but expensive. |
| Approach: | a plug-and-play two-stage hybrid-vector framework is proposed to retrieve visually rich documents . HEAVEN efficiently retrieves candidate pages using a single-vektor method over VS-Pages . it also reranks candidates with a multi-vecctor method while filtering query tokens by linguistic importance . |
| Outcome: | HEAVEN achieves 99.87% of the Recall@1 performance of multi-vector models on average . it reduces per-query computation by 99.8%, achieving efficiency and accuracy . |