Review of: "Fine-Grained Alignment in Vision-and-Language Navigation through Bayesian Optimization"
Wenguan Wang · 2024
To better align language with visual sequence in vision-language-navigation, the paper proposes a Bayesian Optimization-based adversarial optimization framework.This method creates ne-grained vision negatives as data augmentation to enhance the performance of various VLN algorithms.Empirical experiments on R2R and REVERIE demonstrated the e cacy of the proposed framework. Strengths:1.This paper is well-written and highlights good results without grand claims.2. The concept of the BO-based framework is straightforward, and the experimental results validate its utility in enhancing VLN task performance.