arXiv:2207.06226
공식 코드 · Papers with Code
Building a Relation Extraction Baseline for Gene-Disease Associations: A Reproducibility Study
원문 초록
Reproducibility is an important task in scientific research. It is crucial for researchers to compare newly developed systems with the state-of-the-art to assess whether they made a breakthrough. However previous works may not be immediately reproducible, for example due to the lack of source code. In this work we reproduce DEXTER, a system to automatically extract Gene-Disease Associations (GDAs) from biomedical abstracts. The goal is to provide a benchmark for future works regarding Relation Extraction (RE), enabling researchers to test and compare their results.
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Chaining Event Spans for Temporal Relation Grounding
Comparative Analysis of AI Agent Architectures for Entity Relationship Classification
Towards a More Generalized Approach in Open Relation Extraction
Towards Rehearsal-Free Continual Relation Extraction: Capturing Within-Task Variance with Adaptive Prompting
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training
Relation Extraction or Pattern Matching? Unravelling the Generalisation Limits of Language Models for Biographical RE
토론
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