{"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/teacher-student-curriculum-learning","title":"Teacher-Student Curriculum Learning","arxiv_id":"1707.00183","date":"2017-07-01","proceeding":null,"authors":["Tambet Matiisen","Avital Oliver","Taco Cohen","John Schulman"],"abstract":"We propose Teacher-Student Curriculum Learning (TSCL), a framework for\nautomatic curriculum learning, where the Student tries to learn a complex task\nand the Teacher automatically chooses subtasks from a given set for the Student\nto train on. We describe a family of Teacher algorithms that rely on the\nintuition that the Student should practice more those tasks on which it makes\nthe fastest progress, i.e. where the slope of the learning curve is highest. In\naddition, the Teacher algorithms address the problem of forgetting by also\nchoosing tasks where the Student's performance is getting worse. We demonstrate\nthat TSCL matches or surpasses the results of carefully hand-crafted curricula\nin two tasks: addition of decimal numbers with LSTM and navigation in\nMinecraft. Using our automatically generated curriculum enabled to solve a\nMinecraft maze that could not be solved at all when training directly on\nsolving the maze, and the learning was an order of magnitude faster than\nuniform sampling of subtasks.","url_abs":"http://arxiv.org/abs/1707.00183v2","url_pdf":"http://arxiv.org/pdf/1707.00183v2.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":"teacher-student-curriculum-learning","repo_url":"https://github.com/tambetm/TSCL","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"teacher-student-curriculum-learning","repo_url":"https://github.com/lcswillems/automatic-curriculum","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"teacher-student-curriculum-learning","repo_url":"https://github.com/mkunesch/remainder-rnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"minecraft","task_name":"Minecraft"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1707.00183","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1707.00183"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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