Xiwen_liang Contrastive Instruction Trajectory Learning for Vision Language Navigation 2022

[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....

<span title='2023-02-10 02:51:23 +1100 AEDT'>February 10, 2023</span>&nbsp;·&nbsp;2 min&nbsp;·&nbsp;360 words&nbsp;·&nbsp;Sukai Huang
Illustration of DiffCSE

Yung_sung_chuang Diffcse Difference Based Contrastive Learning for Sentence Embeddings 2022

[TOC] Title: DiffCSE: Difference Based Contrastive Learning for Sentence Embeddings Author: Yung-Sung Chuang et. al. Publish Year: 21 Apr 2022 Review Date: Sat, Aug 27, 2022 Summary of paper Motivation DiffCSE learns sentences that are sensitive to the difference between the original sentence and and edited sentence. Contribution we propose DiffCSE, an unsupervised contrastive learning framework for learning sentence embeddings Some key terms DiffCSE this is an unsupervsied contrastive learning framework rather than model architecture Contrastive learning in single modality data...

<span title='2022-08-27 16:03:42 +1000 AEST'>August 27, 2022</span>&nbsp;·&nbsp;2 min&nbsp;·&nbsp;351 words&nbsp;·&nbsp;Sukai Huang