{"as_of":"2026-08-10T14:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:24f8969902ead33f8587f9aa891cd00226c778932fc9be061f954251679d9568","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T22:49:30.207893Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-05-18T22:45:31.935618Z","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":"2026-05-18T22:46:53.151723Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"cited_work":{"arxiv_id":"2501.18712","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18712","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Invisible traces: Using hybrid fingerprinting to identify underlying LLMs in GenAI apps","venue":null,"work_id":"df3af2f0-d882-41fa-8f1d-c3757a957610","year":2025},"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":12,"source":"pdf_text","source_observed_at":"2026-05-18T22:45:31.935618Z"},"links":{"cited_paper":"/paper/2501.18712","citing_paper":"/paper/2508.11548"},"observation_digest":"sha256:4633386dfc60eca5f62561bf193bd3a719b3affee8584e5270a6101fbf35b25e","observation_id":"29ab6aab-6d9a-4b6b-9fbc-47e01fe93bdd","resolution":{"observed_at":"2026-05-18T22:46:53.154790Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"cited_work":{"arxiv_id":"2501.18712","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18712","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Invisible traces: Using hybrid fingerprinting to identify underlying LLMs in GenAI apps","venue":null,"work_id":"df3af2f0-d882-41fa-8f1d-c3757a957610","year":2025},"citing_paper":{"arxiv_id":"2604.10473","last_updated":"2026-04-12T05:59:47Z","snapshot_observed_at":"2026-07-06T22:59:05.519456Z","submitted_at":"2026-04-12T05:59:47Z","title":"AI Identification: An Integrated Framework for Sustainable Governance in Digital Enterprises","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T16:41:11.489564Z"},"links":{"cited_paper":"/paper/2501.18712","citing_paper":"/paper/2604.10473"},"observation_digest":"sha256:fbd7628a6170ac7a9db616f1d326db56a26ac9c3d691bc06c52b637d48ae0906","observation_id":"53d4c322-d83a-45d4-af6a-c845651c4f59","resolution":{"observed_at":"2026-05-11T08:21:01.188243Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.18712/citation-record","integrity":"/paper/2501.18712/integrity","json":"/paper/2501.18712/citation-record.json","paper":"/paper/2501.18712"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:49:30.499554Z","title":"J., et al","venue":null,"work_id":"201baabe-2961-4964-8f83-a34b05b8ac62","year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.132347Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:3a88ccaf56b35be62eac74b03e75d64848af5a0dc6cfeffe670ee8b5adec64f2","observation_id":"d5960c4f-3882-449e-bbfc-aa08bd192e9c","resolution":{"observed_at":"2026-08-09T22:49:30.504783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17541","last_updated":"2024-06-20T02:53:20Z","snapshot_observed_at":"2026-07-06T16:54:18.139849Z","submitted_at":"2023-11-29T11:23:42Z","title":"TaskWeaver: A Code-First Agent Framework","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17541","snapshot_observed_at":"2026-08-09T22:49:30.137212Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.137212Z"},"links":{"cited_paper":"/paper/2311.17541","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:9448fb4e7acee091ef54a12e22e179df41f4ee40ea1b3f9228072f61a79c2d19","observation_id":"c46bffa7-f9db-49d9-9765-aa6675f31020","resolution":{"observed_at":"2026-08-09T22:49:30.137212Z","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":"2026-08-09T22:49:30.141677Z","title":"A., Jagielski, M., Gao, I., Koh, P","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.141677Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:8959d4a5ce812224e1001f8f6a3dacc997503c0727d7a2df15a8ce0f1e9f2aa8","observation_id":"89add857-fd5a-471f-bb31-cb1e851be924","resolution":{"observed_at":"2026-08-09T22:49:30.141677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08419","last_updated":"2024-07-18T18:24:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-12T15:38:28Z","title":"Jailbreaking Black Box Large Language Models in Twenty Queries","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08419","snapshot_observed_at":"2026-08-09T22:49:30.146755Z","title":"J., and Wong, E","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.146755Z"},"links":{"cited_paper":"/paper/2310.08419","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:27de0a6346e80cd81c6021f261f58d034f3af760ffd7b74d3b1c229a54d9793e","observation_id":"713b81ef-9e49-4864-b103-8cb020c0a231","resolution":{"observed_at":"2026-08-09T22:49:30.146755Z","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":"2026-08-09T22:49:30.152098Z","title":"u ttler, H., Lewis, M., Yih, W.-t., Rockt \\","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.152098Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:2ab67e1ed2a2a2fa3de6982341865581f406f11ee38a3113700581c8f8c6c086","observation_id":"beb2e073-a072-41c9-8a14-1ab9d5a0cbe0","resolution":{"observed_at":"2026-08-09T22:49:30.152098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.04451","last_updated":"2024-03-20T21:34:56Z","snapshot_observed_at":"2026-08-06T02:57:30.438059Z","submitted_at":"2023-10-03T19:44:37Z","title":"AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.04451","snapshot_observed_at":"2026-08-09T22:49:30.155882Z","title":"Autodan: Generating stealthy jailbreak prompts on aligned large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.155882Z"},"links":{"cited_paper":"/paper/2310.04451","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:0493aef75e480a89498289a98dca1a040987cf7a28e97907c51176af359cb351","observation_id":"470ddb0d-9fef-4d86-92ec-9126274dc102","resolution":{"observed_at":"2026-08-09T22:49:30.155882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13860","last_updated":"2024-03-10T13:58:08Z","snapshot_observed_at":"2026-07-06T15:31:18.144952Z","submitted_at":"2023-05-23T09:33:38Z","title":"Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13860","snapshot_observed_at":"2026-08-09T22:49:30.160912Z","title":"Jailbreaking chatgpt via prompt engineering: An empirical study","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.160912Z"},"links":{"cited_paper":"/paper/2305.13860","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:b3269113784115754e2c71a850dd50a62d703debb37271d1dfb59a01694e8bcc","observation_id":"79a7a393-a969-4ea0-ab8b-c43fc9133ba6","resolution":{"observed_at":"2026-08-09T22:49:30.160912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14057","last_updated":"2024-05-22T23:02:42Z","snapshot_observed_at":"2026-08-08T02:59:13.474746Z","submitted_at":"2024-05-22T23:02:42Z","title":"Your Large Language Models Are Leaving Fingerprints","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14057","snapshot_observed_at":"2026-08-09T22:49:30.165809Z","title":"Your large language models are leaving fingerprints","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.165809Z"},"links":{"cited_paper":"/paper/2405.14057","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:de6a01bb1775a2203a25249ec4fed38bcf3a69a9101e21337c9d36ecd39bc860","observation_id":"e4e09431-720e-48b4-bfa1-7679a542ba82","resolution":{"observed_at":"2026-08-09T22:49:30.165809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15847","last_updated":"2025-02-10T19:42:35Z","snapshot_observed_at":"2026-07-06T18:50:13.559866Z","submitted_at":"2024-07-22T17:59:45Z","title":"LLMmap: Fingerprinting For Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15847","snapshot_observed_at":"2026-08-09T22:49:30.170229Z","title":"M., and Ateniese, G","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.170229Z"},"links":{"cited_paper":"/paper/2407.15847","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:9e1a793d93a67ed128a773d8f048ac74b9ef9ca111f3c6fed466c4d8f6fb9455","observation_id":"6b6e45a5-8cbb-466d-bca1-cba373221bd6","resolution":{"observed_at":"2026-08-09T22:49:30.170229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10887","last_updated":"2026-07-01T11:06:54Z","snapshot_observed_at":"2026-08-09T07:11:34.903048Z","submitted_at":"2024-07-15T16:38:56Z","title":"Hey, That's My Model! Introducing Chain & Hash, An LLM Fingerprinting Technique","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10887","snapshot_observed_at":"2026-08-09T22:49:30.174646Z","title":"and Salem, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.174646Z"},"links":{"cited_paper":"/paper/2407.10887","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:cc2a1adb580a59dc8b40c36812249c45e0716e6b24e7be694b7ebed7319e5b1e","observation_id":"b6db5a8f-78cc-4342-9df5-169cfd75b46b","resolution":{"observed_at":"2026-08-09T22:49:30.174646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13663","last_updated":"2024-12-19T06:32:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-18T09:39:44Z","title":"Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13663","snapshot_observed_at":"2026-08-09T22:49:30.179060Z","title":"Smarter, better, faster, longer: A modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.179060Z"},"links":{"cited_paper":"/paper/2412.13663","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:c08f7cf77700fe8218d9bd552b376aa47bce0545adb8bb6c88309f94f364f842","observation_id":"51b91a0d-7c41-4452-a4b2-aa528422680a","resolution":{"observed_at":"2026-08-09T22:49:30.179060Z","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":"2026-08-09T22:49:30.183156Z","title":"V., Zhou, D., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.183156Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:cdd513994aa2eeee834b42d06100c35d62d5eb8a33c49d61f48e20462e9b1613","observation_id":"afcd5929-6898-44a3-afdb-d410f0b2be70","resolution":{"observed_at":"2026-08-09T22:49:30.183156Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.12255","last_updated":"2024-04-03T06:23:34Z","snapshot_observed_at":"2026-08-10T04:17:45.472447Z","submitted_at":"2024-01-21T09:51:45Z","title":"Instructional Fingerprinting of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.12255","snapshot_observed_at":"2026-08-09T22:49:30.186791Z","title":"D., Koh, P","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.186791Z"},"links":{"cited_paper":"/paper/2401.12255","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:f965bd5501b5bb7e396083d383dd104045ac0227a1c3506cd1a1020ee4958eae","observation_id":"31526ded-671c-443c-9d51-15dc7010d850","resolution":{"observed_at":"2026-08-09T22:49:30.186791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08604","last_updated":"2025-05-16T02:31:25Z","snapshot_observed_at":"2026-07-06T19:31:40.352383Z","submitted_at":"2024-10-11T08:00:49Z","title":"MergePrint: Merge-Resistant Fingerprints for Robust Black-box Ownership Verification of Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08604","snapshot_observed_at":"2026-08-09T22:49:30.191393Z","title":"Mergeprint: Robust fingerprinting against merging large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.191393Z"},"links":{"cited_paper":"/paper/2410.08604","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:96c88c4ff9a19c0fc28dff51dfe499530f8cc6b84c86bde63bc229b54ff70926","observation_id":"9410211b-82ce-4c4c-a904-b4bb07e29434","resolution":{"observed_at":"2026-08-09T22:49:30.191393Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02224","last_updated":"2023-06-04T01:07:20Z","snapshot_observed_at":"2026-08-03T03:58:33.818386Z","submitted_at":"2023-06-04T01:07:20Z","title":"Auto-GPT for Online Decision Making: Benchmarks and Additional Opinions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02224","snapshot_observed_at":"2026-08-09T22:49:30.195363Z","title":"Auto-gpt for online decision making: Benchmarks and additional opinions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.195363Z"},"links":{"cited_paper":"/paper/2306.02224","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:5dbde80331612604006ee500dd4f71590998a4e1864d0e9ca03c1830f792544c","observation_id":"f283d131-8ca1-4613-903a-9a658abbc9ec","resolution":{"observed_at":"2026-08-09T22:49:30.195363Z","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":"2026-08-09T22:49:30.199890Z","title":"and Wu, H","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.199890Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:5e3c963ce472d3f8f032d04a2f787be80fed11830f19859b9618cdb16eadb540","observation_id":"e35930b8-106e-4c44-bc91-f49620f208b0","resolution":{"observed_at":"2026-08-09T22:49:30.199890Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14273","last_updated":"2024-10-18T08:27:02Z","snapshot_observed_at":"2026-07-06T19:35:48.603411Z","submitted_at":"2024-10-18T08:27:02Z","title":"REEF: Representation Encoding Fingerprints for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14273","snapshot_observed_at":"2026-08-09T22:49:30.203351Z","title":"Reef: Representation encoding fingerprints for large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.203351Z"},"links":{"cited_paper":"/paper/2410.14273","citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:9fd0d840ab0159a721e11dc699b4cdda995675308ab5ea208086ba0853ca917b","observation_id":"41974ded-1c93-4a11-a830-33ccefec5fb1","resolution":{"observed_at":"2026-08-09T22:49:30.203351Z","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":"2026-08-09T22:49:30.207893Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps","version":4},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-09T22:49:30.207893Z"},"links":{"citing_paper":"/paper/2501.18712"},"observation_digest":"sha256:47e9a5222d658e82357d2951750301b6c69718ee04838b87d2d12713200111cd","observation_id":"db98aeb4-7b2a-4c2d-b3ad-405b7b9336e0","resolution":{"observed_at":"2026-08-09T22:49:30.207893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.18712","last_updated":"2025-02-07T14:14:07Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T04:18:27.000860Z","submitted_at":"2025-01-30T19:15:41Z","title":"Invisible Traces: Using Hybrid Fingerprinting to identify underlying LLMs in GenAI Apps"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":1},"total_outbound_references":18},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 2 inbound Pith citation observations for arXiv:2501.18712."}