{"as_of":"2026-08-22T16:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:720df281c52b040ddfa8878e7a824cd79539e98c7269cb41f658dfd5a86b9109","coverage":[{"denominator":27,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:01:07.481560Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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":"2026-06-26T09:50:07.322483Z","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":"2026-07-04T09:39:45.921821Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"cited_work":{"arxiv_id":"2506.20197","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20197","snapshot_observed_at":"2026-07-04T09:39:45.921821Z","title":"Lingjiao Chen, Matei Zaharia, and James Zou","venue":null,"work_id":"50d396ea-bbaa-4bd5-ae73-541d1745f642","year":2023},"citing_paper":{"arxiv_id":"2606.22698","last_updated":"2026-06-21T22:24:55Z","snapshot_observed_at":"2026-08-07T00:10:39.468136Z","submitted_at":"2026-06-21T22:24:55Z","title":"Black-Box Forensics for Conversational LLM Agents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-26T09:50:07.322483Z"},"links":{"cited_paper":"/paper/2506.20197","citing_paper":"/paper/2606.22698"},"observation_digest":"sha256:fb8c4d4773cd4e0f9c1413836f712e31e2882f06f332e4884709eed177520ce1","observation_id":"383f04f3-b9df-4a15-b625-26e7ad4b965a","resolution":{"observed_at":"2026-07-04T09:39:45.923729Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.20197/citation-record","integrity":"/paper/2506.20197/integrity","json":"/paper/2506.20197/citation-record.json","paper":"/paper/2506.20197"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.05130","last_updated":"2024-12-16T02:20:31Z","snapshot_observed_at":"2026-08-18T11:53:41.715016Z","submitted_at":"2023-10-08T11:41:28Z","title":"Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05130","snapshot_observed_at":"2026-08-06T23:01:07.292204Z","title":"Fast-detectgpt: Efficient zero-shot detection of machine-generated text via conditional probability curvature","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.292204Z"},"links":{"cited_paper":"/paper/2310.05130","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:102bfd65fec79160ff12f91ff5cf4a5da78e99ddfff71618d18ecfc73bf2d897","observation_id":"5cf20b5c-5fe1-4112-96c5-8bff875fcc42","resolution":{"observed_at":"2026-08-06T23:01:07.292204Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.614377Z","title":"The complexity of approximating the entropy","venue":null,"work_id":"8a963470-832d-439a-a76d-33c3e11758c5","year":2005},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.300247Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:f91c5b290f810415692c016991243500cd388d4aec09c59a447569ce0bce0f39","observation_id":"2aafa2cb-56cb-41b9-a43f-0c4135a114e8","resolution":{"observed_at":"2026-08-06T23:01:08.625643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.588664Z","title":"Efficient distance approximation for structured high-dimensional distributions via learning","venue":null,"work_id":"bf1eab10-0f0e-4c40-bf81-f931884808e3","year":2020},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.307386Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:3357035fdb071dc95175dfeed18bf5915205a7e304299e9373fa89897c2af340","observation_id":"0905fc9e-dad7-4ecc-9cbb-62ff645de5e3","resolution":{"observed_at":"2026-08-06T23:01:08.596523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.563184Z","title":"Canonne and Ronitt Rubinfeld","venue":null,"work_id":"7cb139d1-f9a4-4c91-a41b-c611d91417f9","year":2014},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.314278Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:8e27f3dc517b3b19d0bb7ac292f3dac042978882ffdb34ef54c65bba9f8428a7","observation_id":"d7c524b5-774b-4a26-bafe-a3904ae1d2f3","resolution":{"observed_at":"2026-08-06T23:01:08.571079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"4074.26341","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.137466Z","title":"Canonne, Dana Ron, and Rocco A","venue":null,"work_id":"7891b5ed-9284-4bc8-95c6-0227609e796e","year":2014},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.319889Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:10ff58130e82ad2f6b4462a96eca05c343af182e58108b82de3be6185477b4fb","observation_id":"d779b980-fe2a-4b51-a5f0-be49f36dbb6b","resolution":{"observed_at":"2026-08-06T23:01:08.156402Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.13414","last_updated":"2021-11-09T01:28:01Z","snapshot_observed_at":"2026-08-16T18:14:36.039231Z","submitted_at":"2021-06-25T03:59:42Z","title":"The Price of Tolerance in Distribution Testing","version":2},"cited_work":{"arxiv_id":"2106.13414","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.13414","snapshot_observed_at":"2026-08-06T23:01:08.018357Z","title":"The Price of Tolerance in Distribution Testing","venue":"cs.DS","work_id":"04030769-99cf-46fd-8715-0adbf683e424","year":2021},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.324988Z"},"links":{"cited_paper":"/paper/2106.13414","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:a1c3e9761bbecf2fd1dc07ea6da38298b3f8446cb28d981cb1e40fab6ab6766c","observation_id":"49da855e-ee62-4d6b-b8f3-fa060f4be947","resolution":{"observed_at":"2026-08-06T23:01:08.033905Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.541227Z","title":"Canonne, Ayush Jain, Gautam Kamath, and Jerry Li","venue":null,"work_id":"5068d587-03bd-443e-bf32-265bb7431d6c","year":2022},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.331357Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:a4ccf06a83a7a028e0996f593989341d72ac366b8be8f71d0b6038fbfacef5ce","observation_id":"41a3b4ee-f63d-4131-b72f-7863f8972ba8","resolution":{"observed_at":"2026-08-06T23:01:08.548271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-20T20:50:23.483838Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-06T23:01:07.338773Z","title":"Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William H","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.338773Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:9c8fc2595e6cc31270baff816a631f4951098719462edb9fdb3ea450ecebeb29","observation_id":"d2cca4a2-13dc-45af-b713-8b58190bbd3d","resolution":{"observed_at":"2026-08-06T23:01:07.338773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:07.344907Z","title":"Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator","venue":null,"work_id":null,"year":1956},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.344907Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:b81f14954929588c3340e1303c2dc570b13d7152cd0f6701020068c8c9b01f7d","observation_id":"f29c7d87-ce75-4eae-a055-ac630ca9c05a","resolution":{"observed_at":"2026-08-06T23:01:07.344907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11606","last_updated":"2025-04-03T15:07:13Z","snapshot_observed_at":"2026-08-19T01:12:39.732067Z","submitted_at":"2024-07-16T11:12:28Z","title":"The Foundations of Tokenization: Statistical and Computational Concerns","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11606","snapshot_observed_at":"2026-08-06T23:01:07.352057Z","title":"The foundations of tokenization: Statistical and computational concerns","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.352057Z"},"links":{"cited_paper":"/paper/2407.11606","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:0e63a99c259f769af0ec5b9d10d467305a7e4fa5748a90e2f0cf4fdbef971138","observation_id":"ca60473a-12f0-4195-81f2-ac9b902f5f94","resolution":{"observed_at":"2026-08-06T23:01:07.352057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07543","last_updated":"2023-02-10T11:59:31Z","snapshot_observed_at":"2026-08-21T14:05:14.066426Z","submitted_at":"2022-10-14T05:42:39Z","title":"Watermarking Pre-trained Language Models with Backdooring","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.07543","snapshot_observed_at":"2026-08-06T23:01:07.362202Z","title":"Watermarking pre-trained language models with backdooring","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.362202Z"},"links":{"cited_paper":"/paper/2210.07543","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:5c2ba1c64047990f6add24412e37b9e891a1f321d589ca1bb15bc55a345d3474","observation_id":"f056cb75-b59c-4a3d-a54d-6a9b394a09e3","resolution":{"observed_at":"2026-08-06T23:01:07.362202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14196","last_updated":"2024-01-26T09:23:11Z","snapshot_observed_at":"2026-08-06T22:40:28.707813Z","submitted_at":"2024-01-25T14:17:53Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14196","snapshot_observed_at":"2026-08-06T23:01:07.370957Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.370957Z"},"links":{"cited_paper":"/paper/2401.14196","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:ac489b28b808983623ac117171e2dc615fe0c12469445a5f60debf63515ea6a8","observation_id":"de90c0a8-af46-4056-9468-538e685d4b1e","resolution":{"observed_at":"2026-08-06T23:01:07.370957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.04634","last_updated":"2024-05-01T21:20:36Z","snapshot_observed_at":"2026-08-20T23:24:23.818026Z","submitted_at":"2023-06-07T17:58:48Z","title":"On the Reliability of Watermarks for Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.04634","snapshot_observed_at":"2026-08-06T23:01:07.376482Z","title":"On the reliability of watermarks for large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.376482Z"},"links":{"cited_paper":"/paper/2306.04634","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:7cafe431a34aad092afcdadcc1c22cd2aba85a785c8d245e20f225dce0d51972","observation_id":"9124d34e-5dee-4a02-9401-3215b637b0ed","resolution":{"observed_at":"2026-08-06T23:01:07.376482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03164","last_updated":"2023-09-06T17:06:31Z","snapshot_observed_at":"2026-08-16T15:02:46.018115Z","submitted_at":"2023-09-06T17:06:31Z","title":"J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News","version":1},"cited_work":{"arxiv_id":"2309.03164","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.03164","snapshot_observed_at":"2026-08-06T23:01:07.787450Z","title":"J-Guard: Journalism Guided Adversarially Robust Detection of AI-generated News","venue":"cs.CL","work_id":"b12cae8d-22fc-4559-8e57-e2dd22241d9b","year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.381993Z"},"links":{"cited_paper":"/paper/2309.03164","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:05ebfd9eb797e0e5bbd70bd6630e35dbba7f3600086b826e5781119e6d9a067b","observation_id":"17646165-3858-4cfe-830b-0a08bf27cf3c","resolution":{"observed_at":"2026-08-06T23:01:07.798794Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:07.387047Z","title":"The tight constant in the D voretzky-- K iefer-- W olfowitz inequality","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.387047Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:c9d8b5e4ae7fe56e5404325af56294ba9bc560fde9753930fd6cd5fceb9b9dc1","observation_id":"2aa7d378-cc63-4a61-86c5-45ac9e5ab541","resolution":{"observed_at":"2026-08-06T23:01:07.387047Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:07.392793Z","title":"Detectgpt: Zero-shot machine-generated text detection using probability curvature","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.392793Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:e95b02d935a557b2dfd229a54c2dc9ec9879a7304607ee54f88c22de8ae15bf0","observation_id":"a39e38ff-2bdb-47d2-b433-f503137eed31","resolution":{"observed_at":"2026-08-06T23:01:07.392793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.482278Z","title":"Probability-revealing samples","venue":null,"work_id":"67eb26c6-36ce-478f-bcc2-2c7303db47df","year":2018},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.399600Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:a8f5dd3f045339c8349b0d41073ced18c62344f166d47e605883ec7f7f0915f5","observation_id":"c09bd331-db30-451d-af07-e63e20b69137","resolution":{"observed_at":"2026-08-06T23:01:08.492893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.444308Z","title":"Stable code 3b, 2023","venue":null,"work_id":"fcef4054-0d1f-4589-9765-9b40b8256926","year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.406789Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:e2dd1eeaed4bc2f44dfa57baace7c6936f43bc41f1250600e4a48ef797aa1239","observation_id":"d62e2558-56f9-40d6-8227-52d91dbbe1e8","resolution":{"observed_at":"2026-08-06T23:01:08.453928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:07.412200Z","title":"Language models are unsupervised multitask learners","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.412200Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:5e8deb08cdcd9e84f1a69d46f29319209b4eea8ab3db1c4bad589fb38860a099","observation_id":"30b0ace6-cb44-4cd1-ab23-efe44b4c84a2","resolution":{"observed_at":"2026-08-06T23:01:07.412200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1508.07909","last_updated":"2016-06-10T14:45:08Z","snapshot_observed_at":"2026-08-17T07:28:37.146698Z","submitted_at":"2015-08-31T16:37:31Z","title":"Neural Machine Translation of Rare Words with Subword Units","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1508.07909","snapshot_observed_at":"2026-08-06T23:01:07.421910Z","title":"Neural machine translation of rare words with subword units","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.421910Z"},"links":{"cited_paper":"/paper/1508.07909","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:2deb2751eb2d3373a54deac4425cdeaa8b8e80e1804dfca2dc9d8425f4409d88","observation_id":"fe4e35ad-85f6-445b-b301-d2f38d6539a2","resolution":{"observed_at":"2026-08-06T23:01:07.421910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.395055Z","title":"Did you train on my dataset? towards public dataset protection with cleanlabel backdoor watermarking","venue":null,"work_id":"445646fc-4f9d-4ddc-b992-ea4e85f61334","year":2023},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.430063Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:718dae6185f10919e2b77020c954e54846e054b73c473fccf18fb77e5318e8c3","observation_id":"ecf55933-d0df-4a9c-a6e8-c2c462ec18d3","resolution":{"observed_at":"2026-08-06T23:01:08.402102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11409","last_updated":"2024-06-19T02:37:50Z","snapshot_observed_at":"2026-08-16T21:13:11.293578Z","submitted_at":"2024-06-17T10:54:35Z","title":"CodeGemma: Open Code Models Based on Gemma","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11409","snapshot_observed_at":"2026-08-06T23:01:07.435534Z","title":"Codegemma: Open code models based on gemma","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.435534Z"},"links":{"cited_paper":"/paper/2406.11409","citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:8fc0053f1c6e5610ff89636c3d39e9123b2ea3588a4b58506c9d09967f5b011e","observation_id":"5ed6e69e-3880-4471-978b-f110ced5f49e","resolution":{"observed_at":"2026-08-06T23:01:07.435534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.366237Z","title":"Authorship attribution for neural text generation","venue":null,"work_id":"b1687c94-4dea-47c9-b81d-8797e727ddb4","year":2020},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.441336Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:8a3198eec9d9382d1f39ab82eaf2e7af9b6c4d6b4281ed7eb4253b9e1aaed60e","observation_id":"6124b0e0-1cac-4913-8ea3-0b1863dd3b84","resolution":{"observed_at":"2026-08-06T23:01:08.373920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.340833Z","title":"Topformer: Topology-aware authorship attribution of deepfake texts with diverse writing styles","venue":null,"work_id":"47f79fc5-396f-437d-86bf-63fb45cb0f97","year":2024},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.449505Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:5b0b211009212bf7a58202b55e20cc22ee70e9f57e848a1a1018a0a17deb6e08","observation_id":"576353f9-6303-4621-a27a-56ac87eea02e","resolution":{"observed_at":"2026-08-06T23:01:08.348180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.304724Z","title":"Estimating the unseen: An n/ n -sample estimator for entropy and support size, shown optimal via new clts","venue":null,"work_id":"c6b6a6ac-f277-42b6-a237-8a75ee7d03d2","year":2011},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.466737Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:5f271f87d6452f88c4a9c9f2460408826c4530d9df1c783639c3bba57c362a31","observation_id":"e2bbfd28-097d-4fdc-b1d4-67a865a0c501","resolution":{"observed_at":"2026-08-06T23:01:08.314721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:08.257885Z","title":"A survey on llm-generated text detection: Necessity, methods, and future directions","venue":null,"work_id":"b427873d-306c-4296-87c9-8fabbd6d5789","year":2025},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.475523Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:1c5bcf7f747085bfdf8cb783de4db373734e94a20c1ad13a286b4465ff4fc1ac","observation_id":"68a8cf5d-a964-4841-9936-5f3bf80fb0b5","resolution":{"observed_at":"2026-08-06T23:01:08.273330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:01:07.481560Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T23:01:07.481560Z"},"links":{"citing_paper":"/paper/2506.20197"},"observation_digest":"sha256:24648ac93a37a848c151444e2d16170f56ca262a27b372f8c90e3c5fee6a9bbf","observation_id":"92298dca-ccb0-4d1f-89df-96cc5765a0cc","resolution":{"observed_at":"2026-08-06T23:01:07.481560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.20197","last_updated":"2025-06-25T07:37:16Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-20T13:34:13.644000Z","submitted_at":"2025-06-25T07:37:16Z","title":"Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach"},"reference_resolution":{"displayed":27,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":13,"verified_exact":1,"verified_fuzzy":11},"total_outbound_references":27},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2506.20197."}