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Small Models Are (Still) Effective Cross-Domain Argument Extractors
- Publication Year :
- 2024
-
Abstract
- Effective ontology transfer has been a major goal of recent work on event argument extraction (EAE). Two methods in particular -- question answering (QA) and template infilling (TI) -- have emerged as promising approaches to this problem. However, detailed explorations of these techniques' ability to actually enable this transfer are lacking. In this work, we provide such a study, exploring zero-shot transfer using both techniques on six major EAE datasets at both the sentence and document levels. Further, we challenge the growing reliance on LLMs for zero-shot extraction, showing that vastly smaller models trained on an appropriate source ontology can yield zero-shot performance superior to that of GPT-3.5 or GPT-4.<br />Comment: ACL Rolling Review Short Paper
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2404.08579
- Document Type :
- Working Paper