{"as_of":"2026-08-12T05:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7f6ae977da807371fba70ffcd39624b149a800423168337d347aeb45318eae4f","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:31:45.273734Z","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":"2026-08-09T22:54:25.133188Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2403.06403","last_updated":"2025-07-16T11:30:47Z","snapshot_observed_at":"2026-08-11T07:39:15.331399Z","submitted_at":"2024-03-11T03:28:20Z","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.06403","snapshot_observed_at":"2026-08-10T21:31:45.273734Z","title":"Pointseg: A training-free paradigm for 3d scene segmentation via foundation models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.04696","last_updated":"2025-03-08T11:17:47Z","snapshot_observed_at":"2026-08-11T03:37:54.597355Z","submitted_at":"2025-01-08T18:58:24Z","title":"Test-Time Optimization for Domain Adaptive Open Vocabulary Segmentation","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T21:31:45.273734Z"},"links":{"cited_paper":"/paper/2403.06403","citing_paper":"/paper/2501.04696"},"observation_digest":"sha256:4c3a217e47b3dfec006f5241ce781a1a5123579c2c943c20c268703c12612166","observation_id":"de5242b0-acdc-4cef-a619-73830c68c6a3","resolution":{"observed_at":"2026-08-10T21:31:45.273734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.06403","last_updated":"2025-07-16T11:30:47Z","snapshot_observed_at":"2026-08-11T07:39:15.331399Z","submitted_at":"2024-03-11T03:28:20Z","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models","version":5},"cited_work":{"arxiv_id":"2403.06403","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.06403","snapshot_observed_at":"2026-08-09T22:54:25.133188Z","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models","venue":"cs.CV","work_id":"ce71edc8-19c7-4b8d-9141-8d09b9a9005f","year":2024},"citing_paper":{"arxiv_id":"2501.18594","last_updated":"2025-01-30T18:59:43Z","snapshot_observed_at":"2026-08-10T21:33:12.435265Z","submitted_at":"2025-01-30T18:59:43Z","title":"Foundational Models for 3D Point Clouds: A Survey and Outlook","version":1},"reference_index":161,"source":"pdf_text","source_observed_at":"2026-08-09T22:54:24.877034Z"},"links":{"cited_paper":"/paper/2403.06403","citing_paper":"/paper/2501.18594"},"observation_digest":"sha256:b40bc51e810b93bc674eacf31ac1753aa222d1d3f6fc87c2d2992cc0b12542ae","observation_id":"4ce8bb7a-cc4e-4b69-9c3f-ee4b15f5b756","resolution":{"observed_at":"2026-08-09T22:54:25.137260Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2403.06403/citation-record","integrity":"/paper/2403.06403/integrity","json":"/paper/2403.06403/citation-record.json","paper":"/paper/2403.06403"},"outbound":[],"paper":{"arxiv_id":"2403.06403","last_updated":"2025-07-16T11:30:47Z","latest_version":5,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T07:39:15.331399Z","submitted_at":"2024-03-11T03:28:20Z","title":"PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.06403."}