Elamur Research⌕
☰
home / papers / 2026 / GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning

GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning

Paper · 2026 · Fengyi Wu, Yifei Dong, Yilong Dai et al.

Summary

The paper presents GoViG, a new task in which a model must write natural-language route directions using only two first-person images: one of the starting position and one of the destination. Earlier instruction generators relied on maps, semantic annotations or panoramas, or reduced images to text descriptions. These requirements limit their use in unfamiliar, unstructured settings. The authors split the problem into two linked steps. The model first imagines the intermediate views along the route (navigation visualization). It then writes directions grounded in both real and predicted frames. Both steps run inside a single autoregressive multimodal LLM, Anole-7B, trained with a Token Discrepancy Loss for visual prediction and a Label Smoothing Loss for text. At inference, the model either forecasts all frames before writing (one-pass) or alternates frames and instruction fragments (interleaved). For evaluation, the authors release R2R-Goal, which mixes simulated and real-world trajectories. The interleaved variant beats prior systems and general-purpose MLLMs on automatic metrics and in human ratings, and it transfers well to real-world video.

Key points

  • R2R-Goal benchmark: synthetic trajectories come from R2R-CE and HA-R2R, and real egocentric videos come from GO Stanford, ReCon and HuRoN, all annotated with instructions.
  • Unseen split, BLEU-4: interleaved reasoning scores 0.32 and one-pass 0.29, against C-Instructor 0.22, GPT-4o + CoT 0.09 and LANA 0.05. Validation CIDEr for the interleaved variant is 0.20.
  • Zero-shot transfer: on the real-world subset, the interleaved strategy reaches BLEU-4 0.27, ahead of competing methods.
  • User study: 21 raters scored 320 trajectories on a 1–6 scale. Results were interleaved 4.85, one-pass 4.52, GPT-4o + CoT 3.76, Gemini 3.0 3.54, Claude 4 Opus 3.41, C-Instructor 3.08 and LANA 2.67.
  • Limitations: training needs 4×A100 GPUs, only Anole-7B was tested, and the code is available at github.com/F1y1113/GoViG.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓Carnegie Mellon UniversityPittsburgh · United States598 works · 191,226 citations🏢MicrosoftRedmond · United States378 works · 161,630 citations🎓University of WashingtonSeattle · United States402 works · 212,763 citations🎓Hong Kong Polytechnic UniversityHong Kong · China106 works · 5,190 citations🎓University of Washington TacomaTacoma · United States2 works

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 18,614 worksArtificial Intelligence · 17,965 worksArts and Humanities · 17,450 worksLanguage and Linguistics · 17,296 worksComputer Vision and Pattern Recognition · 3,486 works

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 1,685 worksVision & language · 811 works

Cite

Cite as Fengyi Wu, Yifei Dong, Yilong Dai, Guangyu Chen, Qifeng Wu, Huiting Huang, Hang Wang, Qi Dai, Alexander G Hauptmann and Zhi-Qi Cheng. 2026. GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning. Findings of the Association for Computational Linguistics: ACL 2026.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2026.findings-acl.732

@inproceedings{wu2026govig,
  title = {{GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning}},
  author = {Fengyi Wu, Yifei Dong, Yilong Dai, Guangyu Chen, Qifeng Wu, Huiting Huang, Hang Wang, Qi Dai, Alexander G Hauptmann and Zhi-Qi Cheng},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year = {2026},
  doi = {10.18653/v1/2026.findings-acl.732},
  url = {https://doi.org/10.18653/v1/2026.findings-acl.732}
}

References

81 references, 20 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Gary L Allen. 1997. From knowledge to words to wayfinding: Issues in the production and comprehension of route directions. In International Conference on Spatial Information Theory, pages 363–372. Springer. find
  2. Dong An, Yuankai Qi, Yangguang Li, Yan Huang, Liang Wang, Tieniu Tan, and Jing Shao. 2023. Bevbert: Multimodal map pre-training for language-guided navigation. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 2737– 2748. find
  3. Dong An, Hanqing Wang, Wenguan Wang, Zun Wang, Yan Huang, Keji He, and Liang Wang. 2024. Etpnav: Evolving topological planning for vision-language navigation in continuous environments. IEEE Transactions on Pattern Analysis and Machine Intelligence. find
  4. Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, and Anton Van Den Hengel. 2018. Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments. In Proceedings of the IEEE conference on computer visi…
  5. Anthropic. 2024. The claude 3 model family: Opus, sonnet, haiku. https://www-cdn.anthropic.com/ de8ba9b01c9ab7cbabf5c33b80b7bbc618857627/ Model_Card_Claude_3.pdf. Preprint. ↗
  6. Anthropic. 2025. Introducing claude 4: Claude opus 4 and claude sonnet 4. https://www.anthropic.com/news/claude-4. Accessed: January 3, 2026. ↗
  7. Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael Rabbat, Yann LeCun, and Nicolas Ballas. 2023. Self-supervised learning from images with a joint-embedding predictive architecture. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognitio… find
  8. Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, and 1 others. 2025. Qwen2. 5-vl technical report. arXiv preprint arXiv:2502.13923. — Qwen2.5-VL Technical Report
  9. Federico Baldassarre, Marc Szafraniec, Basile Ter-ver, Vasil Khalidov, Francisco Massa, Yann LeCun, Patrick Labatut, Maximilian Seitzer, and Piotr Bojanowski. 2025. Back to the features: Dino as a foundation for video world models. arXiv preprint arXiv:2507.19468. — [arXiv:2507.19468](https://arxiv.org/abs/2507.19468) find
  10. Satanjeev Banerjee and Alon Lavie. 2005. Meteor: An automatic metric for mt evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization, pages 65–72.
  11. Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mahmoud Assran, and Nicolas Ballas. 2024. Revisiting feature prediction for learning visual representations from video. arXiv preprint arXiv:2404.08471. — [arXiv:2404.08471](https://arxiv.org/abs/2404.08471) find
  12. Zhenfang Chen, Qinhong Zhou, Yikang Shen, Yining Hong, Hao Zhang, and Chuang Gan. 2023. See, think, confirm: Interactive prompting between vision and language models for knowledge-based visual reasoning. arXiv preprint arXiv:2301.05226. — [arXiv:2301.05226](https://arxiv.org/abs/2301.05226) find
  13. Ethan Chern, Jiadi Su, Yan Ma, and Pengfei Liu. 2024. Anole: An open, autoregressive, native large multimodal models for interleaved image-text generation. arXiv preprint arXiv:2407.06135. — [arXiv:2407.06135](https://arxiv.org/abs/2407.06135) find
  14. Gheorghe Comanici, Eric Bieber, Mike Schaekermann, Ice Pasupat, Noveen Sachdeva, Inderjit Dhillon, Marcel Blistein, Ori Ram, Dan Zhang, Evan Rosen, and 1 others. 2025. Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities. arX…
  15. Yibo Cui, Liang Xie, Yu Zhao, Jiawei Sun, and Erwei Yin. 2025. Generating vision-language navigation instructions incorporated fine-grained alignment annotations. Preprint, arXiv:2506.08566. — [arXiv:2506.08566](https://arxiv.org/abs/2506.08566) find
  16. Google DeepMind. 2024. Introducing gemini 2.0: A new ai model for the agentic era. https://blog.google/technology/google-deepmind/ google-gemini-ai-update-december-2024. Accessed: January 3, 2026. ↗
  17. Google DeepMind and Google Research. 2025. Gemini 3: Introducing the latest gemini ai model from google. https://blog.google/products/ gemini/gemini-3/. Accessed: January 3, 2026. ↗
  18. Jingtao Ding, Yunke Zhang, Yu Shang, Yuheng Zhang, Zefang Zong, Jie Feng, Yuan Yuan, Hongyuan Su, Nian Li, Nicholas Sukiennik, and 1 others. 2024. find
  19. Understanding world or predicting future? a comprehensive survey of world models. ACM Computing Surveys. find
  20. Yifei Dong, Fengyi Wu, Guangyu Chen, Zhi-Qi Cheng, Qiyu Hu, Yuxuan Zhou, Jingdong Sun, Jun-Yan He, Qi Dai, and Alexander G Hauptmann. 2025a. Unified world models: Memory-augmented planning and foresight for visual navigation. arXiv preprint arXiv:2510.08713. — [arXiv:2510.08713](https://arxiv.org/abs/2510.08713) find
  21. Yifei Dong, Fengyi Wu, Yilong Dai, Lingdong Kong, Guangyu Chen, Xu Zhu, Qiyu Hu, Tianyu Wang, Johnalbert Garnica, Feng Liu, and 1 others. 2026. Language-conditioned world modeling for visual navigation. arXiv preprint arXiv:2603.26741. — [arXiv:2603.26741](https://arxiv.org/abs/2603.26741) find
  22. Yifei Dong, Fengyi Wu, Qi He, Zhi-Qi Cheng, Heng Li, Minghan Li, Zebang Cheng, Yuxuan Zhou, Jingdong Sun, Qi Dai, and 1 others. 2025b. Ha-vln 2.0: An open benchmark and leaderboard for human-aware navigation in discrete and continuous environments with dynamic multi-human interactions. arXiv preprin… — [arXiv:2503.14229](https://arxiv.org/abs/2503.14229) find
  23. Yifei Dong, Fengyi Wu, Kunlin Zhang, Yilong Dai, Sanjian Zhang, Wanghao Ye, Sihan Chen, and Zhi-Qi Cheng. 2025c. Large language model agents in finance: A survey bridging research, practice, and real-world deployment. Findings of the Association for Computational Linguistics: EMNLP, 2025:17889– 1790… find
  24. Sheng Fan, Rui Liu, Wenguan Wang, and Yi Yang. 2024. Navigation instruction generation with bev perception and large language models. In European Conference on Computer Vision, pages 368–387. Springer. find
  25. Sheng Fan, Rui Liu, Wenguan Wang, and Yi Yang. 2025. Scene map-based prompt tuning for navigation instruction generation. In Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), pages 6898–6908. find
  26. Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, and Trevor Darrell. 2018. Speaker-follower models for vision-and-language navigation. Preprint, arXiv:1806.02724. find
  27. Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, and Phillip Isola. 2023. Dreamsim: Learning new dimensions of human visual similarity using synthetic data. arXiv preprint arXiv:2306.09344. — [arXiv:2306.09344](https://arxiv.org/abs/2306.09344) find
  28. Google. 2024. Introducing gemini 2.0: our new ai model for the agentic era. find
  29. Muraleekrishna Gopinathan, Martin Masek, Jumana Abu-Khalaf, and David Suter. 2024. Spatially-aware speaker for vision-and-language navigation instruction generation. arXiv preprint arXiv:2409.05583. find
  30. David Ha and Jürgen Schmidhuber. 2018. World models. arXiv preprint arXiv:1803.10122, 2(3). find
  31. Danijar Hafner, Timothy Lillicrap, Jimmy Ba, and Mohammad Norouzi. 2019. Dream to control: Learning behaviors by latent imagination. arXiv preprint arXiv:1912.01603. find
  32. Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba. 2022. Mastering atari with discrete world models. Preprint, arXiv:2010.02193. find
  33. Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, and Timothy Lillicrap. 2024. Mastering diverse domains through world models. Preprint, arXiv:2301.04104. find
  34. Roberto Henschel, Levon Khachatryan, Daniil Hayrapetyan, Hayk Poghosyan, Vahram Tade-vosyan, Zhangyang Wang, Shant Navasardyan, and Humphrey Shi. 2024. Streamingt2v: Consistent, dynamic, and extendable long video generation from text. arXiv preprint arXiv:2403.14773. — [arXiv:2403.14773](https://arxiv.org/abs/2403.14773) find
  35. Noriaki Hirose, Amir Sadeghian, Marynel Vázquez, Patrick Goebel, and Silvio Savarese. 2018. Gonet: A semi-supervised deep learning approach for traversability estimation. In 2018 IEEE/RSJ international conference on intelligent robots and systems (IROS), pages 3044–3051. IEEE. find
  36. Noriaki Hirose, Dhruv Shah, Ajay Sridhar, and Sergey Levine. 2023. Sacson: Scalable autonomous control for social navigation. IEEE Robotics and Automation Letters, 9(1):49–56. find
  37. Wenyi Hong, Ming Ding, Wendi Zheng, Xinghan Liu, and Jie Tang. 2022. Cogvideo: Large-scale pre-training for text-to-video generation via transformers. arXiv preprint arXiv:2205.15868.
  38. Alain Hore and Djemel Ziou. 2010. Image quality metrics: Psnr vs. ssim. In 2010 20th international conference on pattern recognition, pages 2366–2369. IEEE. find
  39. Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, and 1 others. 2022. Lora: Low-rank adaptation of large language models. ICLR, 1(2):3.
  40. Alycia M Hund and Jennifer L Minarik. 2006. Getting from here to there: Spatial anxiety, wayfinding strategies, direction type, and wayfinding efficiency. Spatial cognition and computation, 6(3):179–201. find
  41. Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, and 1 others. 2024. Gpt-4o system card. arXiv preprint arXiv:2410.21276.
  42. Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris, and Nikos Komodakis. 2024. Dino-foresight: Looking into the future with dino. arXiv preprint arXiv:2412.11673. — [arXiv:2412.11673](https://arxiv.org/abs/2412.11673) find
  43. Xianghao Kong, Jinyu Chen, Wenguan Wang, Hang Su, Xiaolin Hu, Yi Yang, and Si Liu. 2024. Controllable Navigation Instruction Generation with Chain of Thought Prompting, page 37–54. Springer Nature Switzerland. find
  44. Jacob Krantz, Erik Wijmans, Arjun Majundar, Dhruv Batra, and Stefan Lee. 2020. Beyond the nav-graph: Vision and language navigation in continuous environments. In European Conference on Computer Vision (ECCV). find
  45. Chengzu Li, Wenshan Wu, Huanyu Zhang, Yan Xia, Shaoguang Mao, Li Dong, Ivan Vulić, and Furu Wei. 2025. Imagine while reasoning in space: Multimodal visualization-of-thought. arXiv preprint arXiv:2501.07542. — [arXiv:2501.07542](https://arxiv.org/abs/2501.07542) find
  46. Heng Li, Minghan Li, Zhi-Qi Cheng, Yifei Dong, Yuxuan Zhou, Jun-Yan He, Qi Dai, Teruko Mitamura, and Alexander G Hauptmann. 2024. Human-aware vision-and-language navigation: Bridging simulation to reality with dynamic human interactions. Advances in Neural Information Processing Systems, 37:119411–1… find
  47. Jiapeng Li, Ping Wei, Wenjuan Han, and Lifeng Fan. 2023a. Intentqa: Context-aware video intent reasoning. In Proceedings of the IEEE/CVF international conference on computer vision, pages 11963–11974. find
  48. Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023b. Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models. In International conference on machine learning, pages 19730–19742. PMLR.
  49. KunChang Li, Yinan He, Yi Wang, Yizhuo Li, Wenhai Wang, Ping Luo, Yali Wang, Limin Wang, and Yu Qiao. 2023c. Videochat: Chat-centric video understanding. arXiv preprint arXiv:2305.06355.
  50. Chin-Yew Lin. 2004. Rouge: A package for automatic evaluation of summaries. In Text summarization branches out, pages 74–81.
  51. Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023. Visual instruction tuning. Advances in neural information processing systems, 36:34892– 34916.
  52. Kevin Lynch. 1964. The image of the city. MIT press. find
  53. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics, pages 311–318.
  54. Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, and Sergey Levine. 2021. Rapid exploration for open-world navigation with latent goal models. arXiv preprint arXiv:2104.05859. — [arXiv:2104.05859](https://arxiv.org/abs/2104.05859) find
  55. Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong, Letian Wang, Yu Liu, and Hongsheng Li. 2024. Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning. Advances in Neural Information Processing Systems, 37:8612–8642.
  56. Hao Tan, Licheng Yu, and Mohit Bansal. 2019. Learning to navigate unseen environments: Back translation with environmental dropout. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Sh…
  57. Chameleon Team. 2024. Chameleon: Mixed-modal early-fusion foundation models. arXiv preprint arXiv:2405.09818.
  58. Eric J Vanetti and Gary L Allen. 1988. Communicating environmental knowledge: The impact of verbal and spatial abilities on the production and comprehension of route directions. Environment and Behavior, 20(6):667–682. find
  59. Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh. 2015. Cider: Consensus-based image description evaluation. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4566–4575.
  60. Hanqing Wang, Wei Liang, Jianbing Shen, Luc Van Gool, and Wenguan Wang. 2022a. Counterfactual cycle-consistent learning for instruction following and generation in vision-language navigation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 15450–15460. find
  61. Su Wang, Ceslee Montgomery, Jordi Orbay, Vighnesh Birodkar, Aleksandra Faust, Izzeddin Gur, Natasha Jaques, Austin Waters, Jason Baldridge, and Peter Anderson. 2022b. Less is more: Generating grounded navigation instructions from landmarks. In Proceedings of the IEEE/CVF Conference on Computer Visio… find
  62. Xiaohan Wang, Wenguan Wang, Jiayi Shao, and Yi Yang. 2023. Lana: A language-capable navigator for instruction following and generation. Preprint, arXiv:2303.08409. — [arXiv:2303.08409](https://arxiv.org/abs/2303.08409) find
  63. Xiaohan Wang, Wenguan Wang, Jiayi Shao, and Yi Yang. 2024. Learning to follow and generate instructions for language-capable navigation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5):3334–3350. find
  64. Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli. 2004. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600–612. find
  65. Zihan Wang, Yaohui Zhu, Gim Hee Lee, and Yachun Fan. 2025a. Navrag: Generating user demand instructions for embodied navigation through retrieval-augmented llm. Preprint, arXiv:2502.11142. find
  66. Zun Wang, Jialu Li, Yicong Hong, Songze Li, Kunchang Li, Shoubin Yu, Yi Wang, Yu Qiao, Yali Wang, Mohit Bansal, and Limin Wang. 2025b. Bootstrapping language-guided navigation learning with self-refining data flywheel. Preprint, arXiv:2412.08467. find
  67. Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, and 1 others. 2022. Chain-of-thought prompting elicits reasoning in large language models. Advances in neural information processing systems, 35:24824– 24837.
  68. Lai Wei, Wenkai Wang, Xiaoyu Shen, Yu Xie, Zhihao Fan, Xiaojin Zhang, Zhongyu Wei, and Wei Chen. 2024. Mc-cot: A modular collaborative cot framework for zero-shot medical-vqa with llm and mllm integration. arXiv preprint arXiv:2410.04521. — [arXiv:2410.04521](https://arxiv.org/abs/2410.04521) find
  69. Wenshan Wu, Shaoguang Mao, Yadong Zhang, Yan Xia, Li Dong, Lei Cui, and Furu Wei. 2024. Mind’s eye of llms: visualization-of-thought elicits spatial reasoning in large language models. Advances in Neural Information Processing Systems, 37:90277– 90317. find
  70. Eric Xing, Mingkai Deng, Jinyu Hou, and Zhiting Hu. 2025. Critiques of world models. Preprint, arXiv:2507.05169. — [arXiv:2507.05169](https://arxiv.org/abs/2507.05169) find
  71. Yu Yan, Rongtao Xu, Jiazhao Zhang, Peiyang Li, Xiaodan Liang, and Jianqin Yin. 2024. Instrugen: Automatic instruction generation for vision-and-language navigation via large multimodal models. Preprint, arXiv:2411.11394. — [arXiv:2411.11394](https://arxiv.org/abs/2411.11394) find
  72. Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, Zicheng Liu, and Lijuan Wang. 2023a. The dawn of lmms: Preliminary explorations with gpt-4v(ision). Preprint, arXiv:2309.17421.
  73. Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Ehsan Azarnasab, Faisal Ahmed, Zicheng Liu, Ce Liu, Michael Zeng, and Lijuan Wang. 2023b. Mm-react: Prompting chatgpt for multimodal reasoning and action. arXiv preprint arXiv:2303.11381.
  74. Haitian Zeng, Xiaohan Wang, Wenguan Wang, and Yi Yang. 2023. Kefa: A knowledge enhanced and fine-grained aligned speaker for navigation instruction generation. Preprint, arXiv:2307.13368. — [arXiv:2307.13368](https://arxiv.org/abs/2307.13368) find
  75. Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang. 2018. The unreasonable effectiveness of deep features as a perceptual metric. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 586–595. find
  76. Yue Zhang, Ziqiao Ma, Jialu Li, Yanyuan Qiao, Zun Wang, Joyce Chai, Qi Wu, Mohit Bansal, and Parisa Kordjamshidi. 2024. Vision-and-language navigation today and tomorrow: A survey in the era of foundation models. arXiv preprint arXiv:2407.07035. find
  77. Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, and Alex Smola. 2023. Multimodal chain-of-thought reasoning in language models. arXiv preprint arXiv:2302.00923.
  78. Guosheng Zhao, Xiaofeng Wang, Zheng Zhu, Xinze Chen, Guan Huang, Xiaoyi Bao, and Xingang Wang. 2025a. Drivedreamer-2: Llm-enhanced world models for diverse driving video generation. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 10412–10420. find
  79. Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do, Nakul Agarwal, Kwonjoon Lee, and Chen Sun. 2023. Antgpt: Can large language models help long-term action anticipation from videos? arXiv preprint arXiv:2307.16368. — [arXiv:2307.16368](https://arxiv.org/abs/2307.16368) find
  80. Yi Zhao, Siqi Wang, and Jing Li. 2025b. Laf-grpo: In-situ navigation instruction generation for the visually impaired via grpo with llm-as-follower reward. Preprint, arXiv:2506.04070. — [arXiv:2506.04070](https://arxiv.org/abs/2506.04070) find
  81. Qiji Zhou, Ruochen Zhou, Zike Hu, Panzhong Lu, Siyang Gao, and Yue Zhang. 2024. Image-of-thought prompting for visual reasoning refinement in multimodal large language models. arXiv preprint arXiv:2405.13872. — [arXiv:2405.13872](https://arxiv.org/abs/2405.13872) find

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/wu-2026-govig-goal-conditioned-visual-navigation/