8 citations · 16 across the 7 of their papers we have counts for
10 papers · 1 filter
Retrieval-Augmented Generative Question Answering for Event Argument Extraction
Xinya Du, Heng Ji
Event argument extraction has long been studied as a sequential prediction problem with extractive-based methods, tackling each argument in isolation. Although recent work proposes…
Dynamic Global Memory for Document-level Argument Extraction
Xinya Du, Sha Li, Heng Ji
Extracting informative arguments of events from news articles is a challenging problem in information extraction, which requires a global contextual understanding of each document.…
Automatic Error Analysis for Document-level Information Extraction
Aliva Das, Xinya Du, Barry Wang +4
Document-level information extraction (IE) tasks have recently begun to be revisited in earnest using the end-to-end neural network techniques that have been successful on their se…
Few-shot Intent Classification and Slot Filling with Retrieved Examples
Dian Yu, Luheng He, Yuan Zhang +3
Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce…
Improving Event Duration Prediction via Time-aware Pre-training
Zonglin Yang, Xinya Du, Alexander Rush +1
End-to-end models in NLP rarely encode external world knowledge about length of time. We introduce two effective models for duration prediction, which incorporate external knowledg…
GRIT: Generative Role-filler Transformers for Document-level Event Entity Extraction
Xinya Du, Alexander M. Rush, Claire Cardie
We revisit the classic problem of document-level role-filler entity extraction (REE) for template filling. We argue that sentence-level approaches are ill-suited to the task and in…