Charles Chen — accepted AI-conference papers

2022

Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation

Kevin Yang, Olivia Deng, Charles Chen, Richard Shin, Subhro Roy, Benjamin Van Durme

ACL 2022findings

We introduce a novel setup for low-resource task-oriented semantic parsing which incorporates several constraints that may arise in real-world scenarios: (1) lack of similar datasets/models from a related domain, (2) inability to sample useful logical forms directly from a grammar, and (3) privacy r…

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2021

Constrained Language Models Yield Few-Shot Semantic Parsers

Richard Shin, Christopher Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios +4

EMNLP 2021main

We explore the use of large pretrained language models as few-shot semantic parsers. The goal in semantic parsing is to generate a structured meaning representation given a natural language input. However, language models are trained to generate natural language. To bridge the gap, we use language m…

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