Natural Language Understanding

[TOC] Title: Natural Language Decomposition and Interpretation of Complex Utterances Author: Jacob Andreas Publish Year: 15 May 2023 Review Date: Mon, May 22, 2023 url: https://arxiv.org/pdf/2305.08677.pdf Summary of paper Motivation natural language interface often require supervised data to translate user request into structure intent representations however, during data collection, it can be difficult to anticipate and formalise the full range of user needs we introduce an approach for equipping a simple language to code model to handle complex utterances via a process of hierarchical natural language decomposition. Contribution Experiments show that the proposed approach enables the interpretation of complex utterances with almost no complex training data, while outperforming standard few-shot prompting approaches. Some key terms Methodology ...

[TOC] Title: Out of Order: How Important Is The Sequential Order of Words in a Sentence in Natural Language Understanding Tasks? Author: Thang M. Pham Publish Year: Jul 2021 Review Date: Feb 2022 Summary of paper The author found out that BERT-based models trained on GLUE have low sensitivity to word orders. The research questions are the following Do BERT-based models trained on GLUE care about the order of words in a sentence? ANS: NO, except one task named CoLA, which is to detecting grammatically incorrect sentences. Surprisingly, for the rest of the 5 out of 6 binary-classification tasks (i.e. except CoLA), between75% and 90% of the originally correct predictions remain constant after 1-grams are randomly re-ordered Are SOTA BERT-based models using word order information when solving NLU tasks? If not, what cues do they rely on? ANS: they heavily rely on the word itself rather than the ordering. The results showed that if the top - 1 most important word measured by LIME has a positive meaning, then there is 100% probability that the sentence’s label is “positive” Results ...