Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Pages: 9063 - 9074
Published: Nov 5, 2021
Abstract
Recent prompt-based approaches allow pretrained language models to achieve strong performances on few-shot finetuning by reformulating downstream tasks as a language modeling problem. In this work, we demonstrate that, despite its advantages on low data regimes, finetuned prompt-based models for sentence pair classification tasks still suffer from a common pitfall of adopting inference heuristics based on lexical overlap, e.g., models...
Paper Details
Title
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Published Date
Nov 5, 2021
Pages
9063 - 9074
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