3 citations · 7 across the 4 of their papers we have counts for
7 papers
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…
Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding
Xinya Du, Claire Cardie
Few works in the literature of event extraction have gone beyond individual sentences to make extraction decisions. This is problematic when the information needed to recognize an…
Event Extraction by Answering (Almost) Natural Questions
Xinya Du, Claire Cardie
The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments. Existing work in event argument extraction typically relies heavily…
Be Consistent! Improving Procedural Text Comprehension using Label Consistency
Xinya Du, Bhavana Dalvi Mishra, Niket Tandon +4
Our goal is procedural text comprehension, namely tracking how the properties of entities (e.g., their location) change with time given a procedural text (e.g., a paragraph about p…