{"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/build-grid","entry":"build_grid","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":15,"n_papers_ran":11,"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":14,"n_samples_ran":10,"n_samples_fingerprinted":0,"n_places":16,"n_places_pointer_only":8,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":4,"ran_fixture":1,"ran":5,"unverified":4},"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":"2411.07784","paper":"/paper/interaction-asymmetry-a-general-principle-for","title":"Interaction Asymmetry: A General Principle for Learning Composable Abstractions","date":"2024-11-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jackbrady/interaction-asymmetry","path":"models/positional_encodings.py","file_url":"https://github.com/jackbrady/interaction-asymmetry/blob/HEAD/models/positional_encodings.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e4df5adc692667d4","mcp_get_code":{"code_sha256":"e4df5adc692667d4"}},{"arxiv_id":"2405.17283","paper":"/paper/recurrent-complex-weighted-autoencoders-for","title":"Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery","date":"2024-05-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"agopal42/syncx","path":"utils/utils_general.py","file_url":"https://github.com/agopal42/syncx/blob/HEAD/utils/utils_general.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"420dc4b93ae15162","mcp_get_code":{"code_sha256":"420dc4b93ae15162"}},{"arxiv_id":"2403.03458","paper":"/paper/slot-abstractors-toward-scalable-abstract","title":"Slot Abstractors: Toward Scalable Abstract Visual Reasoning","date":"2024-03-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shanka123/slot-abstractor","path":"art/slot_abstractor.py","file_url":"https://github.com/shanka123/slot-abstractor/blob/HEAD/art/slot_abstractor.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a894bb5fa452ee7b","mcp_get_code":{"code_sha256":"a894bb5fa452ee7b"}},{"arxiv_id":"2401.10148","paper":"/paper/explicitly-disentangled-representations-in","title":"Explicitly Disentangled Representations in Object-Centric Learning","date":"2024-01-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"riccardomajellaro/disentangled-slot-attention","path":"models/disa.py","file_url":"https://github.com/riccardomajellaro/disentangled-slot-attention/blob/HEAD/models/disa.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"075b435ce4871df1","mcp_get_code":{"code_sha256":"075b435ce4871df1"}},{"arxiv_id":"2401.10148","paper":"/paper/explicitly-disentangled-representations-in","title":"Explicitly Disentangled Representations in Object-Centric Learning","date":"2024-01-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"riccardomajellaro/disentangled-slot-attention","path":"models/sa.py","file_url":"https://github.com/riccardomajellaro/disentangled-slot-attention/blob/HEAD/models/sa.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"2053ddf28b96b5a1","mcp_get_code":{"code_sha256":"2053ddf28b96b5a1"}},{"arxiv_id":"2308.11796","paper":"/paper/time-does-tell-self-supervised-time-tuning-of","title":"Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations","date":"2023-08-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"smsd75/timetuning","path":"motion_grouping_model.py","file_url":"https://github.com/smsd75/timetuning/blob/HEAD/motion_grouping_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"a51ebb5e1ba6cf37","mcp_get_code":{"code_sha256":"a51ebb5e1ba6cf37"}},{"arxiv_id":"2306.02500","paper":"/paper/systematic-visual-reasoning-through-object-1","title":"Systematic Visual Reasoning through Object-Centric Relational Abstraction","date":"2023-06-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shanka123/ocra","path":"ocra.py","file_url":"https://github.com/shanka123/ocra/blob/HEAD/ocra.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a894bb5fa452ee7b","mcp_get_code":{"code_sha256":"a894bb5fa452ee7b"}},{"arxiv_id":"2304.13892","paper":"/paper/discovering-object-centric-generalized-value","title":"Discovering Object-Centric Generalized Value Functions From Pixels","date":"2023-04-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"somjit77/oc_gvfs","path":"slot_attention/model_jax.py","file_url":"https://github.com/somjit77/oc_gvfs/blob/HEAD/slot_attention/model_jax.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d42ce6eadbd4a112","mcp_get_code":{"code_sha256":"d42ce6eadbd4a112"}},{"arxiv_id":"2303.17842","paper":"/paper/shepherding-slots-to-objects-towards-stable","title":"Shepherding Slots to Objects: Towards Stable and Robust Object-Centric Learning","date":"2023-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"object-understanding/slash","path":"model.py","file_url":"https://github.com/object-understanding/slash/blob/HEAD/model.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"58fa0de4f2f3e646","mcp_get_code":{"code_sha256":"58fa0de4f2f3e646"}},{"arxiv_id":"2303.15555","paper":"/paper/object-discovery-from-motion-guided-tokens","title":"Object Discovery from Motion-Guided Tokens","date":"2023-03-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zpbao/MoTok","path":"models/model.py","file_url":"https://github.com/zpbao/MoTok/blob/HEAD/models/model.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8a1bbc075986fb5f","mcp_get_code":{"code_sha256":"8a1bbc075986fb5f"}},{"arxiv_id":"2303.02260","paper":"/paper/learning-to-reason-over-visual-objects","title":"Learning to reason over visual objects","date":"2023-03-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shanka123/stsn","path":"clevr_slot_transformer.py","file_url":"https://github.com/shanka123/stsn/blob/HEAD/clevr_slot_transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a894bb5fa452ee7b","mcp_get_code":{"code_sha256":"a894bb5fa452ee7b"}},{"arxiv_id":"2301.05169","paper":"/paper/causal-triplet-an-open-challenge-for","title":"Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning","date":"2023-01-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"CausalTriplet/causaltriplet","path":"model/slotpair.py","file_url":"https://github.com/CausalTriplet/causaltriplet/blob/HEAD/model/slotpair.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":"3e53111511bb1304","mcp_get_code":{"code_sha256":"3e53111511bb1304"}},{"arxiv_id":"2209.11924","paper":"/paper/interventional-causal-representation-learning","title":"Interventional Causal Representation Learning","date":"2022-09-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/causalrepid","path":"models/image_slot_attention_decoder.py","file_url":"https://github.com/facebookresearch/causalrepid/blob/HEAD/models/image_slot_attention_decoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"28269a22b2e230e2","mcp_get_code":{"code_sha256":"28269a22b2e230e2"}},{"arxiv_id":"2104.01148","paper":"/paper/decomposing-3d-scenes-into-objects-via","title":"Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation","date":"2021-04-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"stelzner/obsurf","path":"obsurf/layers.py","file_url":"https://github.com/stelzner/obsurf/blob/HEAD/obsurf/layers.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbdaf8f5728d098b","mcp_get_code":{"code_sha256":"fbdaf8f5728d098b"}},{"arxiv_id":"2006.15055","paper":"/paper/object-centric-learning-with-slot-attention","title":"Object-Centric Learning with Slot Attention","date":"2020-06-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"a-imamshah/savi-pytorch","path":"model.py","file_url":"https://github.com/a-imamshah/savi-pytorch/blob/HEAD/model.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"dc25809a5c10c08d","mcp_get_code":{"code_sha256":"dc25809a5c10c08d"}},{"arxiv_id":"2003.05034","paper":"/paper/supermix-supervising-the-mixing-data","title":"SuperMix: Supervising the Mixing Data Augmentation","date":"2020-03-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alldbi/SuperMix","path":"train_student.py","file_url":"https://github.com/alldbi/SuperMix/blob/HEAD/train_student.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9f3e8f8a75b70cea","mcp_get_code":{"code_sha256":"9f3e8f8a75b70cea"}}]}