# Meta-Explore: Exploratory Hierarchical Vision-and-Language Navigation Using Scene Object Spectrum Grounding

arXiv: https://arxiv.org/abs/2303.04077 · HTML: https://mlsanity.com/paper/2303.04077/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 53 of its 71 references that are in the map.
- First posted on arXiv 7 Mar 2023.

## Builds on (most cited first, 30 of 53)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [VQA: Visual Question Answering](https://mlsanity.com/paper/1505.00468/) (2015)
- [Masked-attention Mask Transformer for Universal Image Segmentation](https://mlsanity.com/paper/2112.01527/) (2021)
- [Asynchronous Methods for Deep Reinforcement Learning](https://mlsanity.com/paper/1602.01783/) (2016)
- [ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks](https://mlsanity.com/paper/1908.02265/) (2019)
- [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://mlsanity.com/paper/1908.07490/) (2019)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [Prototypical Contrastive Learning of Unsupervised Representations](https://mlsanity.com/paper/2005.04966/) (2020)
- [On Evaluation of Embodied Navigation Agents](https://mlsanity.com/paper/1807.06757/) (2018)
- [Habitat 2.0: Training Home Assistants to Rearrange their Habitat](https://mlsanity.com/paper/2106.14405/) (2021)
- [Gibson Env: Real-World Perception for Embodied Agents](https://mlsanity.com/paper/1808.10654/) (2018)
- [Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environments](https://mlsanity.com/paper/2004.02857/) (2020)
- [Room-Across-Room: Multilingual Vision-and-Language Navigation with Dense Spatiotemporal Grounding](https://mlsanity.com/paper/2010.07954/) (2020)
- [Speaker-Follower Models for Vision-and-Language Navigation](https://mlsanity.com/paper/1806.02724/) (2018)
- [Embodied Question Answering](https://mlsanity.com/paper/1711.11543/) (2017)
- [REVERIE: Remote Embodied Visual Referring Expression in Real Indoor Environments](https://mlsanity.com/paper/1904.10151/) (2019)
- [Learning to Explore using Active Neural SLAM](https://mlsanity.com/paper/2004.05155/) (2020)
- [Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation](https://mlsanity.com/paper/1811.10092/) (2018)
- [A Recurrent Vision-and-Language BERT for Navigation](https://mlsanity.com/paper/2011.13922/) (2020)
- [History Aware Multimodal Transformer for Vision-and-Language Navigation](https://mlsanity.com/paper/2110.13309/) (2021)
- [First return, then explore](https://mlsanity.com/paper/2004.12919/) (2020)
- [Vision-and-Dialog Navigation](https://mlsanity.com/paper/1907.04957/) (2019)
- [Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments](https://mlsanity.com/paper/1811.12354/) (2018)
- [Neural Topological SLAM for Visual Navigation](https://mlsanity.com/paper/2005.12256/) (2020)
- [Think Global, Act Local: Dual-scale Graph Transformer for Vision-and-Language Navigation](https://mlsanity.com/paper/2202.11742/) (2022)
- [Vision-Language Navigation with Self-Supervised Auxiliary Reasoning Tasks](https://mlsanity.com/paper/1911.07883/) (2019)
- [Self-Monitoring Navigation Agent via Auxiliary Progress Estimation](https://mlsanity.com/paper/1901.03035/) (2019)

## Built on by (most cited first, 18 of 18)

- [ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments](https://mlsanity.com/paper/2304.03047/) (2023)
- [Towards Learning a Generalist Model for Embodied Navigation](https://mlsanity.com/paper/2312.02010/) (2023)
- [Multimodal Fusion and Vision-Language Models: A Survey for Robot Vision](https://mlsanity.com/paper/2504.02477/) (2025)
- [Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives](https://mlsanity.com/paper/2406.05615/) (2024)
- [Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences](https://mlsanity.com/paper/2312.09337/) (2023)
- [RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation](https://mlsanity.com/paper/2412.08591/) (2024)
- [OVER-NAV: Elevating Iterative Vision-and-Language Navigation with Open-Vocabulary Detection and StructurEd Representation](https://mlsanity.com/paper/2403.17334/) (2024)
- [Correctable Landmark Discovery via Large Models for Vision-Language Navigation](https://mlsanity.com/paper/2405.18721/) (2024)
- [FlexVLN: Flexible Adaptation for Diverse Vision-and-Language Navigation Tasks](https://mlsanity.com/paper/2503.13966/) (2025)
- [Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation](https://mlsanity.com/paper/2402.17587/) (2024)
- [PRET: Planning with Directed Fidelity Trajectory for Vision and Language Navigation](https://mlsanity.com/paper/2407.11487/) (2024)
- [NavQ: Learning a Q-Model for Foresighted Vision-and-Language Navigation](https://mlsanity.com/paper/2510.16457/) (2025)
- [CoNav: Collaborative Cross-Modal Reasoning for Embodied Navigation](https://mlsanity.com/paper/2505.16663/) (2025)
- [Trajectory-Diversity-Driven Robust Vision-and-Language Navigation](https://mlsanity.com/paper/2603.15370/) (2026)
- [EvolveNav: Empowering LLM-Based Vision-Language Navigation via Self-Improving Embodied Reasoning](https://mlsanity.com/paper/2506.01551/) (2025)
- [Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIM](https://mlsanity.com/paper/2404.17922/) (2024)
- [Fine-Grained Instruction-Guided Graph Reasoning for Vision-and-Language Navigation](https://mlsanity.com/paper/2503.11006/) (2025)
- [Implicit Geometry Representations for Vision-and-Language Navigation from Web Videos](https://mlsanity.com/paper/2603.09259/) (2026)

## Abstract (arXiv)

The main challenge in vision-and-language navigation (VLN) is how to understand natural-language instructions in an unseen environment. The main limitation of conventional VLN algorithms is that if an action is mistaken, the agent fails to follow the instructions or explores unnecessary regions, leading the agent to an irrecoverable path. To tackle this problem, we propose Meta-Explore, a hierarchical navigation method deploying an exploitation policy to correct misled recent actions. We show that an exploitation policy, which moves the agent toward a well-chosen local goal among unvisited but observable states, outperforms a method which moves the agent to a previously visited state. We also highlight the demand for imagining regretful explorations with semantically meaningful clues. The key to our approach is understanding the object placements around the agent in spectral-domain. Specifically, we present a novel visual representation, called scene object spectrum (SOS), which performs category-wise 2D Fourier transform of detected objects. Combining exploitation policy and SOS features, the agent can correct its path by choosing a promising local goal. We evaluate our method in three VLN benchmarks: R2R, SOON, and REVERIE. Meta-Explore outperforms other baselines and shows significant generalization performance. In addition, local goal search using the proposed spectral-domain SOS features significantly improves the success rate by 17.1% and SPL by 20.6% for the SOON benchmark.