Papers by Fangfang Su
Towards Better Representations for Multi-Label Text Classification with Multi-granularity Information (2023.findings-emnlp)
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| Challenge: | Existing studies have shown that pre-trained language models generate word frequency-oriented text representations, causing texts with different labels to be closely distributed in a narrow region, which is difficult to classify. |
| Approach: | They propose a framework to refine the text representation for multi-label text classification using contrastive learning and multi-task learning modules. |
| Outcome: | The proposed framework improves the quality of the representations and yields stable and competitive improvements. |
OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction (2022.coling-1)
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| Challenge: | Event extraction (EE) is an essential task of information extraction, which aims to extract structured event information from unstructured text. |
| Approach: | They propose a tagging scheme and a model to form EE as word-word relation recognition using parallel grid tapping. |
| Outcome: | The proposed model achieves state-of-the-art on 3 overlapped and nested EE benchmarks and faster than baselines. |
Entity-centered Cross-document Relation Extraction (2022.emnlp-main)
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Fengqi Wang, Fei Li, Hao Fei, Jingye Li, Shengqiong Wu, Fangfang Su, Wenxuan Shi, Donghong Ji, Bo Cai
| Challenge: | Existing methods for relation extraction only use text snippets surrounding target entities in multiple documents. |
| Approach: | They propose a relation-extraction model that uses cross-path entity relation attention to detect the semantic relations between entities in a given text. |
| Outcome: | The proposed method outperforms the state-of-the-art methods in the dataset CodRED by 10%. |