{"as_of":"2026-08-09T18:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d6cb51179da15df7811ba9756dd5fb4ce336d43f4486df24d46307912e75bb2c","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:30:13.820538Z","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":"2026-07-04T04:09:34.592296Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.00089","snapshot_observed_at":"2026-08-07T10:30:13.820538Z","title":"Watermarking techniques for large language models: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05242","last_updated":"2025-06-05T17:01:28Z","snapshot_observed_at":"2026-08-09T06:38:54.187923Z","submitted_at":"2025-06-05T17:01:28Z","title":"SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T10:30:13.820538Z"},"links":{"cited_paper":"/paper/2409.00089","citing_paper":"/paper/2506.05242"},"observation_digest":"sha256:866ae17828dfcbe7a0c2c7c0bd34e69aed57f7a596537a07a31af40bfeb0dfdb","observation_id":"cdcda08a-356b-4496-9ab1-61e08432b8e4","resolution":{"observed_at":"2026-08-07T10:30:13.820538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.00089","snapshot_observed_at":"2026-08-06T13:21:26.144007Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.20762","last_updated":"2025-07-28T12:16:52Z","snapshot_observed_at":"2026-08-06T13:21:25.180625Z","submitted_at":"2025-07-28T12:16:52Z","title":"Watermarking Large Language Model-based Time Series Forecasting","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T13:21:26.144007Z"},"links":{"cited_paper":"/paper/2409.00089","citing_paper":"/paper/2507.20762"},"observation_digest":"sha256:b043504aae99034e8fb6df43681c55da2faccd3da65e82c4bb482e9c37fe848a","observation_id":"6b66ec76-4704-4d84-bb8a-678e90af440b","resolution":{"observed_at":"2026-08-06T13:21:26.144007Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2409.00089","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.00089","snapshot_observed_at":"2026-07-04T04:09:34.592296Z","title":null,"venue":null,"work_id":"8dab440e-33e5-438a-adf6-36677650882b","year":2024},"citing_paper":{"arxiv_id":"2508.11548","last_updated":"2026-04-07T07:06:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-15T15:50:20Z","title":"Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-18T22:45:31.935618Z"},"links":{"cited_paper":"/paper/2409.00089","citing_paper":"/paper/2508.11548"},"observation_digest":"sha256:16fe0011cd7fd467bf170b92da2d8b89b8b0ad53b48fdf6578662318b54714d3","observation_id":"e02fe4e0-59a6-46d0-84a1-70a0e9acd6d4","resolution":{"observed_at":"2026-05-18T22:46:53.297861Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2409.00089","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.00089","snapshot_observed_at":"2026-07-04T04:09:34.592296Z","title":null,"venue":null,"work_id":"8dab440e-33e5-438a-adf6-36677650882b","year":2024},"citing_paper":{"arxiv_id":"2604.23568","last_updated":"2026-04-26T07:16:44Z","snapshot_observed_at":"2026-07-06T23:09:48.137856Z","submitted_at":"2026-04-26T07:16:44Z","title":"Green-Red Watermarking for Recommender Systems","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T05:33:40.420853Z"},"links":{"cited_paper":"/paper/2409.00089","citing_paper":"/paper/2604.23568"},"observation_digest":"sha256:776e69bc4c93ac3584a8b13d6c720eebbf0a9f7f6b1dedb0126fa71086aa9c9e","observation_id":"c6ac6c94-70ae-42df-8dfb-db2441657320","resolution":{"observed_at":"2026-05-11T21:26:17.378098Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":"2409.00089","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.00089","snapshot_observed_at":"2026-07-04T04:09:34.592296Z","title":null,"venue":null,"work_id":"8dab440e-33e5-438a-adf6-36677650882b","year":2024},"citing_paper":{"arxiv_id":"2606.20897","last_updated":"2026-06-18T19:45:28Z","snapshot_observed_at":"2026-08-01T22:17:51.886515Z","submitted_at":"2026-06-18T19:45:28Z","title":"PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-26T17:12:38.192534Z"},"links":{"cited_paper":"/paper/2409.00089","citing_paper":"/paper/2606.20897"},"observation_digest":"sha256:d4dd8eab466fe25372a09460e3390620ad43e61d72b613178550cdce768fd9d2","observation_id":"50f5c2c6-18fb-4a73-b8e6-660e80b6ad98","resolution":{"observed_at":"2026-07-04T04:09:34.594933Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.00089/citation-record","integrity":"/paper/2409.00089/integrity","json":"/paper/2409.00089/citation-record.json","paper":"/paper/2409.00089"},"outbound":[],"paper":{"arxiv_id":"2409.00089","last_updated":"2024-08-26T06:50:11Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T04:48:01.110470Z","submitted_at":"2024-08-26T06:50:11Z","title":"Watermarking Techniques for Large Language Models: A Survey"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.00089."}