{"as_of":"2026-08-13T21:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cd4839365d02a081365ad63ce0f39e59d391f0cda4d4d94a285e8ca200188e69","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:56:19.825275Z","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":"2026-08-07T12:56:21.937598Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.03807","last_updated":"2023-11-08T15:23:10Z","snapshot_observed_at":"2026-08-13T14:50:25.943367Z","submitted_at":"2023-05-05T19:20:29Z","title":"Evading Watermark based Detection of AI-Generated Content","version":5},"cited_work":{"arxiv_id":"2305.03807","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.03807","snapshot_observed_at":"2026-08-07T12:56:21.937598Z","title":"Evading Watermark based Detection of AI-Generated Content","venue":"cs.LG","work_id":"08c0fa4b-b295-4664-b7e2-9f46ef6ad37d","year":2023},"citing_paper":{"arxiv_id":"2505.23192","last_updated":"2025-05-29T07:31:17Z","snapshot_observed_at":"2026-08-12T02:55:35.845919Z","submitted_at":"2025-05-29T07:31:17Z","title":"Fooling the Watchers: Breaking AIGC Detectors via Semantic Prompt Attacks","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T12:56:19.825275Z"},"links":{"cited_paper":"/paper/2305.03807","citing_paper":"/paper/2505.23192"},"observation_digest":"sha256:2abdbe8b0c4e0883c1235fece7203a417b37744fade0007bca62f07b38868fa4","observation_id":"ba66880b-1ada-41ca-a685-34dfbb48cb14","resolution":{"observed_at":"2026-08-07T12:56:22.128118Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.03807/citation-record","integrity":"/paper/2305.03807/integrity","json":"/paper/2305.03807/citation-record.json","paper":"/paper/2305.03807"},"outbound":[],"paper":{"arxiv_id":"2305.03807","last_updated":"2023-11-08T15:23:10Z","latest_version":5,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-13T14:50:25.943367Z","submitted_at":"2023-05-05T19:20:29Z","title":"Evading Watermark based Detection of AI-Generated Content"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2305.03807."}