{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/learning-to-stop-a-simple-yet-effective","title":"Learning to Stop: A Simple yet Effective Approach to Urban Vision-Language Navigation","arxiv_id":"2009.13112","date":"2020-09-28","proceeding":"Findings of the Association for Computational Linguistics 2020","authors":["Jiannan Xiang","Xin Eric Wang","William Yang Wang"],"abstract":"Vision-and-Language Navigation (VLN) is a natural language grounding task where an agent learns to follow language instructions and navigate to specified destinations in real-world environments. A key challenge is to recognize and stop at the correct location, especially for complicated outdoor environments. Existing methods treat the STOP action equally as other actions, which results in undesirable behaviors that the agent often fails to stop at the destination even though it might be on the right path. Therefore, we propose Learning to Stop (L2Stop), a simple yet effective policy module that differentiates STOP and other actions. Our approach achieves the new state of the art on a challenging urban VLN dataset Touchdown, outperforming the baseline by 6.89% (absolute improvement) on Success weighted by Edit Distance (SED).","url_abs":"https://arxiv.org/abs/2009.13112v3","url_pdf":"https://arxiv.org/pdf/2009.13112v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"navigate","task_name":"Navigate"},{"task_slug":"vision-and-language-navigation","task_name":"Vision and Language Navigation"},{"task_slug":"vision-language-navigation","task_name":"Vision-Language Navigation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/vision-and-language-navigation-on-touchdown","task":"Vision and Language Navigation","dataset":"Touchdown Dataset","model":"ARC + L2STOP","rank_in_archive_order":4,"of":12,"metrics":{"Task Completion (TC)":"16.68"},"uses_additional_data":false},{"leaderboard":"/sota/vision-and-language-navigation-on-touchdown","task":"Vision and Language Navigation","dataset":"Touchdown Dataset","model":"ARC","rank_in_archive_order":7,"of":12,"metrics":{"Task Completion (TC)":"14.13"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2009.13112","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}