{"as_of":"2026-08-08T03:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:950ca63f96f5a18965a04f53e6c526d8daaf054ad48354512b5485c77056ef1d","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:30:08.526952Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T10:49:45.858121Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.10537","last_updated":"2020-03-06T09:11:04Z","snapshot_observed_at":"2026-07-06T08:31:39.300566Z","submitted_at":"2019-10-23T12:58:08Z","title":"Robust Visual Domain Randomization for Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10537","snapshot_observed_at":"2026-08-06T22:30:08.526952Z","title":"Robust visual domain randomization for reinforcement learning","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.21367","last_updated":"2025-06-26T15:16:35Z","snapshot_observed_at":"2026-08-06T22:23:44.435650Z","submitted_at":"2025-06-26T15:16:35Z","title":"rQdia: Regularizing Q-Value Distributions With Image Augmentation","version":1},"reference_index":2003,"source":"pdf_text","source_observed_at":"2026-08-06T22:30:08.526952Z"},"links":{"cited_paper":"/paper/1910.10537","citing_paper":"/paper/2506.21367"},"observation_digest":"sha256:4d573ae7d8655308d7bec11ad7cf58f0431653dc4f26e7851047f3314df60304","observation_id":"fe8444bd-b67f-4325-85f5-477cedc76b01","resolution":{"observed_at":"2026-08-06T22:30:08.526952Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10537","last_updated":"2020-03-06T09:11:04Z","snapshot_observed_at":"2026-07-06T08:31:39.300566Z","submitted_at":"2019-10-23T12:58:08Z","title":"Robust Visual Domain Randomization for Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10537","snapshot_observed_at":"2026-07-12T13:42:27.758405Z","title":"CovariateShiftAdaptationbyImportanceWeightedCrossValidation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.16933","last_updated":"2026-07-06T13:15:11Z","snapshot_observed_at":"2026-08-06T16:01:13.657296Z","submitted_at":"2026-06-15T16:32:40Z","title":"A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-12T13:42:27.758405Z"},"links":{"cited_paper":"/paper/1910.10537","citing_paper":"/paper/2606.16933"},"observation_digest":"sha256:d0afcf9b320dba67232c228678b1e791a19230a8a9939ef82c8d3e97737520db","observation_id":"42f31156-41a3-4296-8f03-76e8db2bb1f9","resolution":{"observed_at":"2026-07-12T13:42:27.758405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10537","last_updated":"2020-03-06T09:11:04Z","snapshot_observed_at":"2026-07-06T08:31:39.300566Z","submitted_at":"2019-10-23T12:58:08Z","title":"Robust Visual Domain Randomization for Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"1910.10537","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1910.10537","snapshot_observed_at":"2026-07-04T10:49:45.858121Z","title":"Clements, Jakob N","venue":null,"work_id":"338b96ed-f42e-49d2-8274-88c1c7cd2c6b","year":1910},"citing_paper":{"arxiv_id":"2606.22948","last_updated":"2026-06-22T07:28:55Z","snapshot_observed_at":"2026-08-02T18:06:18.563667Z","submitted_at":"2026-06-22T07:28:55Z","title":"ENVS: Environment-Native Verified Search for Long-Horizon GUI Agents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-26T08:29:33.351797Z"},"links":{"cited_paper":"/paper/1910.10537","citing_paper":"/paper/2606.22948"},"observation_digest":"sha256:45ee0592cd24561cd9a8b54d2e470eb124e0075f05dbc287e179774ca5fcc185","observation_id":"d4acbdbc-4eef-4af6-8cce-b1d19df08228","resolution":{"observed_at":"2026-07-04T10:49:45.859628Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10537","last_updated":"2020-03-06T09:11:04Z","snapshot_observed_at":"2026-07-06T08:31:39.300566Z","submitted_at":"2019-10-23T12:58:08Z","title":"Robust Visual Domain Randomization for Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10537","snapshot_observed_at":"2026-08-01T21:28:13.118239Z","title":"Robust vi- sual domain randomization for reinforcement learning,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.16090","last_updated":"2026-07-17T16:20:08Z","snapshot_observed_at":"2026-08-08T00:12:47.557262Z","submitted_at":"2026-07-17T16:20:08Z","title":"DADiff: Diffusion-Driven Cross-Domain Policy Adaptation for Reinforcement Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T21:28:13.118239Z"},"links":{"cited_paper":"/paper/1910.10537","citing_paper":"/paper/2607.16090"},"observation_digest":"sha256:85698eb3d1bf340c6b2ce0382c6719eeea632ae423ebccf207a39859c0ecc1fe","observation_id":"2b5cd315-ee7d-4e0f-a8fc-3a4cc7c89521","resolution":{"observed_at":"2026-08-01T21:28:13.118239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1910.10537/citation-record","integrity":"/paper/1910.10537/integrity","json":"/paper/1910.10537/citation-record.json","paper":"/paper/1910.10537"},"outbound":[],"paper":{"arxiv_id":"1910.10537","last_updated":"2020-03-06T09:11:04Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T08:31:39.300566Z","submitted_at":"2019-10-23T12:58:08Z","title":"Robust Visual Domain Randomization for Reinforcement Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.10537."}