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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Stage-wise Fine-tuning for Graph-to-Text Generation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ji, Heng; Lin, Victoria. - : Underline Science Inc., 2021 BASE Show details 2 HySPA: Hybrid Span Generation for Scalable Text-to-Graph Extraction ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Hockenmaier, Julia; Ji, Heng. - : Underline Science Inc., 2021 BASE Show details 3 InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bansal, Mohit; Chang, Shih-Fu. - : Underline Science Inc., 2021 BASE Show details 4 Learning Shared Semantic Space for Speech-to-Text Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Han, Chi; Ji, Heng. - : Underline Science Inc., 2021 BASE Show details 5 Joint Biomedical Entity and Relation Extraction with Knowledge-Enhanced Collective Inference ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ji, Heng; Lai, Tuan. - : Underline Science Inc., 2021 BASE Show details 6 Event-Centric Natural Language Processing ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Chen, Muhao; Ji, Heng. - : Underline Science Inc., 2021 BASE Show details 7 VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ferritto, Anthony; Florian, Radu. - : Underline Science Inc., 2021 BASE Show details 8 Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Elsayed, Ahmed; Ji, Heng; Myers, Skatje; Palmer, Martha; Parulian, Nikolaus; Zhang, Zixuan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.489 Abstract: Biomedical Information Extraction from scientific literature presents two unique and non-trivial challenges. First, compared with general natural language texts, sentences from scientific papers usually possess wider contexts between knowledge elements. Moreover, comprehending the fine-grained scientific entities and events urgently requires domain-specific background knowledge. In this paper, we propose a novel biomedical Information Extraction (IE) model to tackle these two challenges and extract scientific entities and events from English research papers. We perform Abstract Meaning Representation (AMR) to compress the wide context to uncover a clear semantic structure for each complex sentence. Besides, we construct the sentence-level knowledge graph from an external knowledge base and use it to enrich the AMR graph to improve the model's understanding of complex scientific concepts. We use an edge-conditioned graph attention network to ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://dx.doi.org/10.48448/1k4g-2x17 https://underline.io/lecture/25938-fine-grained-information-extraction-from-biomedical-literature-based-on-knowledge-enriched-abstract-meaning-representation BASE Hide details

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