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Lihong He

2 accepted papers

2023

Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture

EMNLP 2023long findings

Real-world domain experts (e.g., doctors) rarely annotate only a decision label in their day-to-day workflow without providing explanations. Yet, existing low-resource learning techniques, such as Active Learning (AL), that aim to support human annotators mostly focus on the label while neglecting t…

Cited by 0SourcecodeScholar
2022

COIN – an Inexpensive and Strong Baseline for Predicting Out of Vocabulary Word Embeddings

COLING 2022main

Social media is the ultimate challenge for many natural language processing tools. The constant emergence of linguistic constructs challenge even the most sophisticated NLP tools. Predicting word embeddings for out of vocabulary words is one of those challenges. Word embedding models only include te…

Cited by 0SourcePDFScholar