{"as_of":"2026-08-15T15:19:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4373e6fe3ab4187cee5cb9fb5e290a3d806749887d12a822f1c0ad856229ba4b","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T10:05:56.438484Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2411.19583/citation-record","integrity":"/paper/2411.19583/integrity","json":"/paper/2411.19583/citation-record.json","paper":"/paper/2411.19583"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:57.072525Z","title":"Towards learning rubik’s cube with n-tuple-based reinforcement learning, 2023","venue":null,"work_id":"7781282b-f82c-48d5-9aa5-e3f8f74e8d1a","year":2023},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.264220Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:543df4a40d0413b9ab84e9ff5b8fae8c70b5c011ab88265c20ff56ab14a966e3","observation_id":"17ac68ac-f07b-4bad-aaf7-f096870eabda","resolution":{"observed_at":"2026-08-12T10:05:57.082592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:57.038125Z","title":"Solving the rubik’s cube with deep reinforcement learning and search","venue":null,"work_id":"166cb7ff-6ebf-44be-b5ea-e964f68b90b7","year":2019},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.280034Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:b32684cd9d6621d4faf49c4b42b5b6d1dedbee9870e18df79631dc57606512fd","observation_id":"7cdbb064-fcd8-4b36-8fb2-3704b41aa985","resolution":{"observed_at":"2026-08-12T10:05:57.045222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:57.006388Z","title":"Solving the rubik’s cube with approximate policy iteration","venue":null,"work_id":"76b5f06f-ede4-4f44-9ab4-b8fdb53c3485","year":2019},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.299080Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:6c67d3c0db78b11bf8d71573b4bb5ab6d444e3eaf3180320e8931be6bce7d989","observation_id":"1059a4e3-31a4-492d-b3ed-36783c38e210","resolution":{"observed_at":"2026-08-12T10:05:57.017693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00324","last_updated":"2024-07-08T20:15:46Z","snapshot_observed_at":"2026-08-14T06:32:18.825758Z","submitted_at":"2024-06-29T05:55:33Z","title":"Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00324","snapshot_observed_at":"2026-08-12T10:05:56.312431Z","title":"Rupam Mahmood","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.312431Z"},"links":{"cited_paper":"/paper/2407.00324","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:acec2ba3cdbaeb338b1efcd5f53026affbac1ddc3e732b3c5aebfc4eb481ad51","observation_id":"8906dfd2-bd7c-46f0-b2af-6252886c686f","resolution":{"observed_at":"2026-08-12T10:05:56.312431Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.10567","last_updated":"2018-02-28T18:15:49Z","snapshot_observed_at":"2026-08-14T19:41:01.781290Z","submitted_at":"2018-02-28T18:15:49Z","title":"Learning by Playing - Solving Sparse Reward Tasks from Scratch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.10567","snapshot_observed_at":"2026-08-12T10:05:56.321215Z","title":"Learning by Playing - Solving Sparse Reward Tasks from Scratch","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.321215Z"},"links":{"cited_paper":"/paper/1802.10567","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:960d52042f0e7dddc53f2af42fbe424fbeb6a98259ab0fc9fdcdce39b6e83f8a","observation_id":"66ef88f1-1606-4cf7-a9a0-47ebec86de2b","resolution":{"observed_at":"2026-08-12T10:05:56.321215Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.01495","last_updated":"2018-02-23T10:04:20Z","snapshot_observed_at":"2026-08-14T21:15:56.405766Z","submitted_at":"2017-07-05T17:55:53Z","title":"Hindsight Experience Replay","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.01495","snapshot_observed_at":"2026-08-12T10:05:56.333776Z","title":"Hindsight Experience Replay","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.333776Z"},"links":{"cited_paper":"/paper/1707.01495","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:23e340db92cc03ecd89b77a89bccf1e011f569dac1aa5a0e6a8bd79bdc1be887","observation_id":"486a708c-6c63-4e84-9434-e66184847831","resolution":{"observed_at":"2026-08-12T10:05:56.333776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.966928Z","title":"The diameter of the rubik’s cube group is twenty","venue":null,"work_id":"8c282ed4-4764-425f-8dce-a76196d60976","year":2014},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.352569Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:4856fdbadd2dbe2bbf053794d11635fb1c9cbb8ea09a58a97de5c2ab0d4d9096","observation_id":"f9a51eb6-48c9-4bf7-bde2-9ce3743493c7","resolution":{"observed_at":"2026-08-12T10:05:56.985746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.918073Z","title":"Bertsekas and J.N","venue":null,"work_id":"ccd550f1-bcc0-4b02-aa76-ad441578fd4e","year":1995},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.361268Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:baf1312777aa6f556dede946bdd138b405213785b882eab83b3dccfbac1b8555","observation_id":"893c86c9-a8fa-472d-9dfe-ef1f9d3cf440","resolution":{"observed_at":"2026-08-12T10:05:56.925043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.885571Z","title":"Bagnell, Sham M Kakade, Jeff Schneider, and Andrew Ng","venue":null,"work_id":"09fc63b4-15a9-4655-9547-193c21ad23cb","year":2003},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.371263Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:402244e9c43ec27a7426db97433a0c9a1e70d8dd8cea0b2dd3df8f74783cd6cd","observation_id":"4cdd9ee4-96c5-41ed-92fb-1e57f57f9658","resolution":{"observed_at":"2026-08-12T10:05:56.892354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.848136Z","title":"Kakade and John Langford","venue":null,"work_id":"46286403-1ea8-42fa-bb61-3428a58c6e2a","year":2002},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.382433Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:069c6e5c0924e26a5b7f9f7a5795e02ee2790b5da5e9eb20b388a013744cd84e","observation_id":"b53f6f67-b767-4b9d-b699-83e89597aca7","resolution":{"observed_at":"2026-08-12T10:05:56.859241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1405.2878","last_updated":"2014-05-12T19:11:03Z","snapshot_observed_at":"2026-08-14T23:34:20.992401Z","submitted_at":"2014-05-12T19:11:03Z","title":"Approximate Policy Iteration Schemes: A Comparison","version":1},"cited_work":{"arxiv_id":"1405.2878","doi":null,"metadata_source":"pith","pith_arxiv_id":"1405.2878","snapshot_observed_at":"2026-08-12T10:05:56.584329Z","title":"Approximate Policy Iteration Schemes: A Comparison","venue":"cs.AI","work_id":"4a6a7691-5697-44ea-98b4-38bb9aa5073b","year":2014},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.403972Z"},"links":{"cited_paper":"/paper/1405.2878","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:cf663de383fbcbf946b79a16b023cc8b4923737a40401dd7a6f38053df2586f5","observation_id":"3ddd0cd6-2473-475f-97b8-e5212880ae5f","resolution":{"observed_at":"2026-08-12T10:05:56.593774Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.806220Z","title":"Analysis of classification-based policy iteration algorithms","venue":null,"work_id":"c7f6402d-0455-4a2d-b92c-59fa6cbdbc26","year":2016},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.412824Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:4e334f00609e578bd857b1bb73006723231f4b4334f2f69d59e07d8b03d8880e","observation_id":"0b3c3f13-8455-4ca7-98e9-174bb4a8d77b","resolution":{"observed_at":"2026-08-12T10:05:56.813199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T10:05:56.774725Z","title":"Puterman and Moon Chirl Shin","venue":null,"work_id":"5a59d825-580a-44aa-a420-291b41720eea","year":1978},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.419493Z"},"links":{"citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:855135869cf70eaf0bbeb33b13ea035cc45e6275bb1b703de1bf2c9657b0c873","observation_id":"0684f3f8-4b05-4416-99ce-935525687e8c","resolution":{"observed_at":"2026-08-12T10:05:56.782943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-12T10:05:56.427292Z","title":"Proximal Policy Optimization Algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.427292Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:ee94419e16b7658ddfe0ce5c53828ff9cd00b0de6824dbfbd20b32259193b9f1","observation_id":"dd0f3abe-a5c9-4662-9a3f-f448882eef10","resolution":{"observed_at":"2026-08-12T10:05:56.427292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-12T10:05:56.438484Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T10:05:56.438484Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2411.19583"},"observation_digest":"sha256:79527a3c94ebe6c00686d3f7c3c25e83c95f9859938abaa6db554cb01e987b3b","observation_id":"0b4eecf7-d2a9-417d-a3a0-7cc2382601f6","resolution":{"observed_at":"2026-08-12T10:05:56.438484Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.19583","last_updated":"2024-11-29T09:56:40Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T14:29:43.978141Z","submitted_at":"2024-11-29T09:56:40Z","title":"Solving Rubik's Cube Without Tricky Sampling"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":5,"verified_exact":1,"verified_fuzzy":9},"total_outbound_references":15},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2411.19583."}