{"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/neural-task-programming-learning-to","title":"Neural Task Programming: Learning to Generalize Across Hierarchical Tasks","arxiv_id":"1710.01813","date":"2017-10-04","proceeding":null,"authors":["Danfei Xu","Suraj Nair","Yuke Zhu","Julian Gao","Animesh Garg","Li Fei-Fei","Silvio Savarese"],"abstract":"In this work, we propose a novel robot learning framework called Neural Task\nProgramming (NTP), which bridges the idea of few-shot learning from\ndemonstration and neural program induction. NTP takes as input a task\nspecification (e.g., video demonstration of a task) and recursively decomposes\nit into finer sub-task specifications. These specifications are fed to a\nhierarchical neural program, where bottom-level programs are callable\nsubroutines that interact with the environment. We validate our method in three\nrobot manipulation tasks. NTP achieves strong generalization across sequential\ntasks that exhibit hierarchal and compositional structures. The experimental\nresults show that NTP learns to generalize well to- wards unseen tasks with\nincreasing lengths, variable topologies, and changing objectives.","url_abs":"http://arxiv.org/abs/1710.01813v2","url_pdf":"http://arxiv.org/pdf/1710.01813v2.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":[{"paper_slug":"neural-task-programming-learning-to","repo_url":"https://github.com/StanfordVL/arxivbot","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"few-shot-learning","task_name":"Few-Shot Learning"},{"task_slug":"program-induction","task_name":"Program induction"},{"task_slug":"robot-manipulation","task_name":"Robot Manipulation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.01813","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}