{"as_of":"2026-08-21T23:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9898d25a4ad546c061359471a48d790a5fb33d584e1b347659c577bca464a59b","coverage":[{"denominator":4,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T22:24:26.258621Z","state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2605.25740/citation-record","integrity":"/paper/2605.25740/integrity","json":"/paper/2605.25740/citation-record.json","paper":"/paper/2605.25740"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2004.07219","last_updated":"2021-02-06T01:57:28Z","snapshot_observed_at":"2026-08-16T08:32:46.407746Z","submitted_at":"2020-04-15T17:18:19Z","title":"D4RL: Datasets for Deep Data-Driven Reinforcement Learning","version":4},"cited_work":{"arxiv_id":"2004.07219","doi":"10.48550/arxiv.2004.07219","metadata_source":"pith","pith_arxiv_id":"2004.07219","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"D4RL: Datasets for Deep Data-Driven Reinforcement Learning","venue":"cs.LG","work_id":"47082e4e-a4a5-418b-bf4f-4667355065fc","year":2020},"citing_paper":{"arxiv_id":"2605.25740","last_updated":"2026-05-25T11:54:04Z","snapshot_observed_at":"2026-08-13T04:18:08.633945Z","submitted_at":"2026-05-25T11:54:04Z","title":"Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-29T22:24:26.258621Z"},"links":{"cited_paper":"/paper/2004.07219","citing_paper":"/paper/2605.25740"},"observation_digest":"sha256:66d014f8978d8da7d448b470bf9ef3ec096b49a8b5f5675ddc803f6e1e0b149d","observation_id":"79c8ee20-236e-4919-a362-eb5da8c599a2","resolution":{"observed_at":"2026-06-29T22:34:02.574506Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.08415","last_updated":"2023-06-06T01:53:32Z","snapshot_observed_at":"2026-08-13T19:48:28.322536Z","submitted_at":"2016-06-27T19:20:40Z","title":"Gaussian Error Linear Units (GELUs)","version":5},"cited_work":{"arxiv_id":"1606.08415","doi":"10.18653/v1/n19-1122","metadata_source":"pith","pith_arxiv_id":"1606.08415","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Gaussian Error Linear Units (GELUs)","venue":"cs.LG","work_id":"0466fd22-03a1-4a61-af0a-a900e77bb023","year":2016},"citing_paper":{"arxiv_id":"2605.25740","last_updated":"2026-05-25T11:54:04Z","snapshot_observed_at":"2026-08-13T04:18:08.633945Z","submitted_at":"2026-05-25T11:54:04Z","title":"Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T22:24:26.258621Z"},"links":{"cited_paper":"/paper/1606.08415","citing_paper":"/paper/2605.25740"},"observation_digest":"sha256:3370ce998329220732a8082f6a1896e8688af4522241e900c65eafd5e1b47dfa","observation_id":"523fe043-e578-44f1-96de-410a84d360bf","resolution":{"observed_at":"2026-06-29T22:34:02.572261Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.00177","last_updated":"2019-10-07T20:23:21Z","snapshot_observed_at":"2026-08-20T03:06:00.034814Z","submitted_at":"2019-10-01T02:23:38Z","title":"Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning","version":3},"cited_work":{"arxiv_id":"1910.00177","doi":"10.48550/arxiv.1910.00177","metadata_source":"pith","pith_arxiv_id":"1910.00177","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning","venue":"cs.LG","work_id":"ab561983-ab59-4f04-a11e-a467ddde4848","year":2019},"citing_paper":{"arxiv_id":"2605.25740","last_updated":"2026-05-25T11:54:04Z","snapshot_observed_at":"2026-08-13T04:18:08.633945Z","submitted_at":"2026-05-25T11:54:04Z","title":"Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T22:24:26.258621Z"},"links":{"cited_paper":"/paper/1910.00177","citing_paper":"/paper/2605.25740"},"observation_digest":"sha256:15cbe47000caa8acb262f179aad11dd7e6d0de7685b4435be58a4781048ba6ab","observation_id":"b834d788-2b3c-4755-9f14-1fc4e4f59649","resolution":{"observed_at":"2026-06-29T22:34:02.578067Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T22:24:26.258621Z","title":"Zhang, L., Yang, G., and Stadie, B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2605.25740","last_updated":"2026-05-25T11:54:04Z","snapshot_observed_at":"2026-08-13T04:18:08.633945Z","submitted_at":"2026-05-25T11:54:04Z","title":"Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-29T22:24:26.258621Z"},"links":{"citing_paper":"/paper/2605.25740"},"observation_digest":"sha256:1f75b74225daeef99a81707c6e0d38e96dd67b4585d4038e9f0df6ffa7fe6682","observation_id":"64b0739c-8e79-4915-adda-6b5652b67993","resolution":{"observed_at":"2026-06-29T22:24:26.258621Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2605.25740","last_updated":"2026-05-25T11:54:04Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T04:18:08.633945Z","submitted_at":"2026-05-25T11:54:04Z","title":"Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning"},"reference_resolution":{"displayed":4,"state_counts":{"malformed_identifier":1,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":0,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":4},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2605.25740."}