Papers by Xinhang Li
Granular Entity Mapper: Advancing Fine-grained Multimodal Named Entity Recognition and Grounding (2024.findings-emnlp)
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| Challenge: | Existing methods for fine-grained content extraction are limited by long-tailed distribution of textual entity categories and performance of object detectors. |
| Approach: | They propose a multi-granularity entity recognition module and a reranking module to integrate hierarchical information of entity categories, visual cues, and external textual resources collectively. |
| Outcome: | The proposed framework achieves state-of-the-art on the fine-grained content extraction task. |
Visualization Recommendation with Prompt-based Reprogramming of Large Language Models (2024.acl-long)
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| Challenge: | Traditional visualization recommendations require extensive manual maintenance and yet fail to fully comprehend tabular data. |
| Approach: | They propose a hierarchical table prompt-based reprogramming framework that integrates tabular data into LLMs through a strategically crafted prompt learning method. |
| Outcome: | The proposed framework achieves state-of-the-art performance and will be made publicly available upon acceptance. |