{"as_of":"2026-08-18T03:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:39fad8975522bd648186e675e965812e300bf099cde2221c54c7adba8265db5b","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:23:49.093097Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T20:08:12.682290Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.12831","last_updated":"2024-03-09T16:15:38Z","snapshot_observed_at":"2026-08-16T14:56:00.404223Z","submitted_at":"2023-10-02T06:06:32Z","title":"ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets","version":4},"cited_work":{"arxiv_id":"2311.12831","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.12831","snapshot_observed_at":"2026-08-06T20:08:12.682290Z","title":"ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets","venue":"cs.CV","work_id":"bced5f80-950e-4238-903d-cbf658b3a07f","year":2023},"citing_paper":{"arxiv_id":"2507.03836","last_updated":"2025-07-04T23:23:26Z","snapshot_observed_at":"2026-08-17T12:59:43.934948Z","submitted_at":"2025-07-04T23:23:26Z","title":"F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:08:11.584966Z"},"links":{"cited_paper":"/paper/2311.12831","citing_paper":"/paper/2507.03836"},"observation_digest":"sha256:6aafa440bad49c19b62b7982855f40f2034d1c01e099577a0d07d79afcd364b5","observation_id":"330e138c-b696-4a1c-a902-a37463dfc5ce","resolution":{"observed_at":"2026-08-06T20:08:12.687772Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12831","last_updated":"2024-03-09T16:15:38Z","snapshot_observed_at":"2026-08-16T14:56:00.404223Z","submitted_at":"2023-10-02T06:06:32Z","title":"ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12831","snapshot_observed_at":"2026-07-31T19:32:02.358418Z","title":"Tang and C","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.28047","last_updated":"2026-07-30T11:27:06Z","snapshot_observed_at":"2026-08-17T01:15:21.118114Z","submitted_at":"2026-07-30T11:27:06Z","title":"A Query-Efficient Stochastic Volume Rendering Framework for Time-Varying Implicit Neural Volumes","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-31T19:32:02.358418Z"},"links":{"cited_paper":"/paper/2311.12831","citing_paper":"/paper/2607.28047"},"observation_digest":"sha256:5ad7e52ac47724ecd10f5947469a04ee1e57503b528eec1532778ccfeceb80e8","observation_id":"ff690fc5-80fc-469d-b5ea-0045ca12cfd8","resolution":{"observed_at":"2026-07-31T19:32:02.358418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12831","last_updated":"2024-03-09T16:15:38Z","snapshot_observed_at":"2026-08-16T14:56:00.404223Z","submitted_at":"2023-10-02T06:06:32Z","title":"ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12831","snapshot_observed_at":"2026-08-16T00:23:49.093097Z","title":"ECNR: Efficient compressive neu- ral representation of time-varying volumetric datasets.arXiv preprint arXiv:2311.12831, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.12142","last_updated":"2026-08-12T14:59:57Z","snapshot_observed_at":"2026-08-17T04:58:26.914749Z","submitted_at":"2026-08-12T14:59:57Z","title":"Topology-Preserving Meshing of Implicit Scalar Fields via Monotonicity Constraints","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T00:23:49.093097Z"},"links":{"cited_paper":"/paper/2311.12831","citing_paper":"/paper/2608.12142"},"observation_digest":"sha256:2e500c42f18db4458296dfcd8bb801c468edb95a681b8de2a4c3b2c689245ede","observation_id":"0ceeddc9-3437-41fd-863f-a2bfd6d6bfdf","resolution":{"observed_at":"2026-08-16T00:23:49.093097Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2311.12831/citation-record","integrity":"/paper/2311.12831/integrity","json":"/paper/2311.12831/citation-record.json","paper":"/paper/2311.12831"},"outbound":[],"paper":{"arxiv_id":"2311.12831","last_updated":"2024-03-09T16:15:38Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T14:56:00.404223Z","submitted_at":"2023-10-02T06:06:32Z","title":"ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets"},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.12831."}