Data Augmentation

[TOC] Title: Contrastive Instruction Trajectory Learning for Vision Language Navigation Author: Xiwen Liang et. al. Publish Year: AAAI 2022 Review Date: Fri, Feb 10, 2023 url: https://arxiv.org/abs/2112.04138 Summary of paper Motivation previous works learn to navigate step-by-step following an instruction. However, these works may fail to discriminate the similarities and discrepancies across instruction-trajectory pairs and ignore the temporal continuity of sub-instructions. These problems hinder agents from learning distinctive vision-and-language representations, Contribution we propose a coarse-grained contrastive learning objective to enhance vision-and-language representations by contrasting semantics of full trajectory observations and instructions respectively; a fine-grained contrastive learning objective to perceive instructions by leveraging the temporal information of the sub-instructions....

[TOC] Title: Towards Tracing Factual Knowledge in Language Models Back to the Training Data Author: Ekin Akyurek et. al. Publish Year: EMNLP 2022 Review Date: Wed, Feb 8, 2023 url: https://aclanthology.org/2022.findings-emnlp.180.pdf Summary of paper Motivation LMs have been shown to memorize a great deal of factual knowledge contained in their training data. But when an LM generates an assertion, it is often difficult to determine where it learned this information and whether it is true....