{"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":"/code/encode-gif","entry":"encode_gif","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":7,"n_papers_ran":1,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":6,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":5},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2410.10076","paper":"/paper/videoagent-self-improving-video-generation","title":"VideoAgent: Self-Improving Video Generation","date":"2024-10-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"video-as-agent/videoagent","path":"flowdiffusion/feedback_binary_rf.py","file_url":"https://github.com/video-as-agent/videoagent/blob/HEAD/flowdiffusion/feedback_binary_rf.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"42b1783a347ad0d9","mcp_get_code":{"code_sha256":"42b1783a347ad0d9"}},{"arxiv_id":"2306.09205","paper":"/paper/reward-free-curricula-for-training-robust","title":"Reward-Free Curricula for Training Robust World Models","date":"2023-06-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"danijar/dreamerv2","path":"dreamerv2/common/logger.py","file_url":"https://github.com/danijar/dreamerv2/blob/HEAD/dreamerv2/common/logger.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8c937e50ed534047","mcp_get_code":{"code_sha256":"8c937e50ed534047"}},{"arxiv_id":"2210.12566","paper":"/paper/solving-continuous-control-via-q-learning","title":"Solving Continuous Control via Q-learning","date":"2022-10-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tseyde/decqn","path":"decqn/misc/utils.py","file_url":"https://github.com/tseyde/decqn/blob/HEAD/decqn/misc/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"d9ce91cb115d80d5","mcp_get_code":{"code_sha256":"d9ce91cb115d80d5"}},{"arxiv_id":"2110.09514","paper":"/paper/discovering-and-achieving-goals-via-world","title":"Discovering and Achieving Goals via World Models","date":"2021-10-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"orybkin/lexa","path":"lexa/tools.py","file_url":"https://github.com/orybkin/lexa/blob/HEAD/lexa/tools.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"427c760e638127dd","mcp_get_code":{"code_sha256":"427c760e638127dd"}},{"arxiv_id":"2106.07156","paper":"/paper/temporal-predictive-coding-for-model-based","title":"Temporal Predictive Coding For Model-Based Planning In Latent Space","date":"2021-06-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tung-nd/TPC-tensorflow","path":"tools.py","file_url":"https://github.com/tung-nd/TPC-tensorflow/blob/HEAD/tools.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f30faaa0a3610e6d","mcp_get_code":{"code_sha256":"f30faaa0a3610e6d"}},{"arxiv_id":"2001.08726","paper":"/paper/interpretable-end-to-end-urban-autonomous","title":"Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning","date":"2020-01-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cjy1992/interp-e2e-driving","path":"interp_e2e_driving/utils/gif_utils.py","file_url":"https://github.com/cjy1992/interp-e2e-driving/blob/HEAD/interp_e2e_driving/utils/gif_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"93dde1403b38e053","mcp_get_code":{"code_sha256":"93dde1403b38e053"}},{"arxiv_id":"1912.01603","paper":"/paper/dream-to-control-learning-behaviors-by-latent","title":"Dream to Control: Learning Behaviors by Latent Imagination","date":"2019-12-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"danijar/dreamer","path":"tools.py","file_url":"https://github.com/danijar/dreamer/blob/HEAD/tools.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"427c760e638127dd","mcp_get_code":{"code_sha256":"427c760e638127dd"}}]}