Sep 27, 2021 · Under this new evaluation framework, we re-evaluate several state-of-the-art few-shot methods for NLU tasks. Our framework reveals new insights: ...

We introduce an evaluation framework that improves previous evaluation procedures in three key aspects, ie, test performance, dev-test correlation, and ...

FewNLU is an integrated toolkit designed for few-shot natural language understanding (Few-Shot NLU). It contains implementations of a number of state-of-the-art ...

FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding ... state-of-the-art few-shot NLU methods under this. 081 common ...

... This paper is about improving current practices regarding benchmarks of NLP systems. As pointed out by (Ruder, 2021) , benchmarks are made of datasets, ...

To address this issue, we introduce an evaluation framework that improves previous evaluation procedures in three key aspects, i.e., test performance, dev-test ...

An integrated toolkit designed for few-shot natural language understanding. It contains implementation of several state-of-the-art methods, data processing ...

Mar 15, 2022 · To aid reproducing our results and benchmarking few-shot NLU methods, we open-source FewNLU, a toolkit that contains implementations of a number.

FewGLUE consists of a random selection of 32 training examples from the SuperGLUE training sets and up to 20,000 unlabeled examples for each SuperGLUE task.

Sep 27, 2021 · The few-shot natural language understanding. (NLU) task has attracted much recent attention. However, prior methods have been evaluated.