# Generating Contextually-Relevant Navigation Instructions for Blind and Low Vision People

arXiv: https://arxiv.org/abs/2407.08219 · HTML: https://mlsanity.com/paper/2407.08219/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 22 references that are in the map.
- First posted on arXiv 11 Jul 2024.

## Builds on (most cited first, 8 of 8)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [VizWiz Grand Challenge: Answering Visual Questions from Blind People](https://mlsanity.com/paper/1802.08218/) (2018)
- [Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language](https://mlsanity.com/paper/2204.00598/) (2022)
- [Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth](https://mlsanity.com/paper/2201.07436/) (2022)
- [Worst of Both Worlds: Biases Compound in Pre-trained Vision-and-Language Models](https://mlsanity.com/paper/2104.08666/) (2021)
- [Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics](https://mlsanity.com/paper/2205.10646/) (2022)
- [Deep Learning based Wearable Assistive System for Visually Impaired People](https://mlsanity.com/paper/1908.03364/) (2019)
- [Towards Robotic Companions: Understanding Handler-Guide Dog Interactions for Informed Guide Dog Robot Design](https://mlsanity.com/paper/2402.06790/) (2024)

## Built on by (most cited first, 7 of 7)

- [WalkVLM:Aid Visually Impaired People Walking by Vision Language Model](https://mlsanity.com/paper/2412.20903/) (2024)
- [Less Redundancy: Boosting Practicality of Vision Language Model in Walking Assistants](https://mlsanity.com/paper/2508.16070/) (2025)
- [Multilingual Vision-Language Models, A Survey](https://mlsanity.com/paper/2509.22123/) (2025)
- [Exploring the Use of VLMs for Navigation Assistance for People with Blindness and Low Vision](https://mlsanity.com/paper/2603.15624/) (2026)
- [Urban Risk-Aware Navigation via VQA-Based Event Maps for People with Low Vision](https://mlsanity.com/paper/2605.11782/) (2026)
- [VIABLE: A Visually Impaired Assistance Benchmark for VLM-as-a-Judge Evaluation](https://mlsanity.com/paper/2605.31351/) (2026)
- [How Blind and Low-Vision Individuals Prefer Large Vision-Language Model-Generated Scene Descriptions](https://mlsanity.com/paper/2502.14883/) (2025)

## Abstract (arXiv)

Navigating unfamiliar environments presents significant challenges for blind and low-vision (BLV) individuals. In this work, we construct a dataset of images and goals across different scenarios such as searching through kitchens or navigating outdoors. We then investigate how grounded instruction generation methods can provide contextually-relevant navigational guidance to users in these instances. Through a sighted user study, we demonstrate that large pretrained language models can produce correct and useful instructions perceived as beneficial for BLV users. We also conduct a survey and interview with 4 BLV users and observe useful insights on preferences for different instructions based on the scenario.