{"as_of":"2026-08-10T07:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3383ee6343d65e4c1bb7c8a5ea2cfc8812f88d9ca83812e0713e8572912e535f","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T13:07:11.652209Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2509.00973/citation-record","integrity":"/paper/2509.00973/integrity","json":"/paper/2509.00973/citation-record.json","paper":"/paper/2509.00973"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.20297","last_updated":"2024-10-27T00:39:24Z","snapshot_observed_at":"2026-07-06T19:40:12.973874Z","submitted_at":"2024-10-27T00:39:24Z","title":"Fine-Tuning and Evaluating Open-Source Large Language Models for the Army Domain","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.20297","snapshot_observed_at":"2026-08-05T13:07:10.349429Z","title":"Fine-tuning and evaluating open-source large lan- guage models for the army domain,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.349429Z"},"links":{"cited_paper":"/paper/2410.20297","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:93fd98aba0b5248f18cb0d9e5dd4cafae9fd597d9fb74257836306c3b777f362","observation_id":"ed9ac893-2661-4f44-9966-5792fe3ac15c","resolution":{"observed_at":"2026-08-05T13:07:10.349429Z","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":"2026-08-05T13:07:14.019141Z","title":"Leveraging large language models for integrated satellite-aerial-terrestrial networks: recent advances and future directions,","venue":null,"work_id":"70db9207-54a3-443f-a009-efa6701456f2","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.393354Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:6e38c17e30d6011641a55692aea82d65bb0816d428cf91aad3ed9d4e1336f6ff","observation_id":"bba18956-fd6a-460c-a974-1ef23a2bb6a7","resolution":{"observed_at":"2026-08-05T13:07:14.110219Z","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":"2501.16588","last_updated":"2025-01-28T00:02:00Z","snapshot_observed_at":"2026-08-06T20:50:58.814407Z","submitted_at":"2025-01-28T00:02:00Z","title":"Fine-Tuned Language Models as Space Systems Controllers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.16588","snapshot_observed_at":"2026-08-05T13:07:10.477254Z","title":"Fine-tuned language models as space systems con- trollers,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.477254Z"},"links":{"cited_paper":"/paper/2501.16588","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:8c1a5c4188cf1ae8a30d69b8930e726f5d6cf146dcc5c34aa26ad026c7ef1516","observation_id":"360cd618-54d5-49f1-a5e7-721c4d37b479","resolution":{"observed_at":"2026-08-05T13:07:10.477254Z","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":"2026-08-05T13:07:10.539648Z","title":"Milchat: Introducing chain of thought reasoning and grpo to a multimodal small language model for remote sensing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.539648Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:211198513af170720c1230d1f31e35df1af863588e940f8d5838066bdea45bb9","observation_id":"1b44b653-a3c7-4b7e-b31a-e3ca3dee67a0","resolution":{"observed_at":"2026-08-05T13:07:10.539648Z","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":"2026-08-05T13:07:13.840181Z","title":"Pllm- cs: Pre-trained large language model (llm) for cyber threat detection in satellite networks,","venue":null,"work_id":"5c1e6beb-b153-478d-9bfd-5f7925bde254","year":2025},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.601552Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:1b085b4d142694e8687cef25299c5373da5f7e10c150926bb8e6efde97057a10","observation_id":"837f4ad3-77c1-4055-9cd6-dc65d64b0aba","resolution":{"observed_at":"2026-08-05T13:07:13.934074Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:13.657524Z","title":"Stealing part of a production language model,","venue":null,"work_id":"58bebd63-cc39-4f2c-8442-4ed9c83afbbc","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.663729Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:6052b0e01d13e45a874f2f41c51b5234cf1dd4f0f8c0851e8c75dc207f671d5c","observation_id":"742ca975-02a7-4f03-ab9d-b1c19c4b4c78","resolution":{"observed_at":"2026-08-05T13:07:13.704683Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:13.495220Z","title":"Teach llms to phish: Stealing private information from language mod- els,","venue":null,"work_id":"3ff6d739-4613-4a88-8702-efe73cfd6750","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.692289Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:00b331b445fed995dbe9cd7f5b938f81845167bc8d1e0e42865bdbf107d0cfa9","observation_id":"a3f02d56-85b5-411b-a39c-1b1155b5979f","resolution":{"observed_at":"2026-08-05T13:07:13.576129Z","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":"2411.07536","last_updated":"2024-11-12T04:25:31Z","snapshot_observed_at":"2026-08-09T13:19:00.328443Z","submitted_at":"2024-11-12T04:25:31Z","title":"Model Stealing for Any Low-Rank Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.07536","snapshot_observed_at":"2026-08-05T13:07:10.757582Z","title":"Model stealing for any low-rank language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.757582Z"},"links":{"cited_paper":"/paper/2411.07536","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:ab8f4d812aa53d1946d132770df857948b68de013e7611e5edbbf7ab1db7a4ee","observation_id":"384aabe0-4484-491b-b339-ad00f4a0eb43","resolution":{"observed_at":"2026-08-05T13:07:10.757582Z","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":"2026-08-05T13:07:13.306411Z","title":"I know what you trained last summer: A survey on stealing machine learning models and defences,","venue":null,"work_id":"d2c89f0a-0917-4ff0-8910-3130f75b346d","year":2023},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.820299Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:85e0d7a3599f46f5d8825cc215d7b179432d7bf3000a8530777619f702bb4af1","observation_id":"c0ee1942-8ddf-4c72-8f5a-3b996dae19f3","resolution":{"observed_at":"2026-08-05T13:07:13.384999Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:13.162190Z","title":"Privacy backdoors: stealing data with corrupted pretrained models,","venue":null,"work_id":"624d84aa-1fed-4e7f-966d-7b4e21adcb8b","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.873576Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:c43ece31d6eca47404f6382a0b25efe65a77b637c56595a257a1270241b1f20a","observation_id":"e65321c9-69f1-432f-9500-e6c6cbf9822a","resolution":{"observed_at":"2026-08-05T13:07:13.227323Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:13.038892Z","title":"Can’t steal? cont-steal! contrastive stealing attacks against image encoders,","venue":null,"work_id":"8b553c3a-bdc7-4e0f-97de-7899015b5dee","year":2023},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.908447Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:abc24f17b337987d09efb29f690ea82ea5c470a6196b7e50de969d565d5c4364","observation_id":"19c1a9b9-b1d0-4069-b048-6c2ca16b70bc","resolution":{"observed_at":"2026-08-05T13:07:13.089314Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.941889Z","title":"Large language models for link stealing attacks against graph neural networks,","venue":null,"work_id":"bfad2d43-6e3c-4a77-9963-92b417cab83c","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:10.961820Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:a481e1c233060db8b69ff87e00934620b55a886f86a87ab0c15ddc22d2925491","observation_id":"4375ffac-c6ec-46aa-8e18-48c53d30c22b","resolution":{"observed_at":"2026-08-05T13:07:12.981756Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.844543Z","title":"Forensic analysis of indirect prompt injection attacks on llm agents,","venue":null,"work_id":"c0e5a108-56af-4b0d-8969-84abdd75895f","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.025594Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:321d065a5cb7f8c6b6f98acde2f5679311781194a73304a4b9dbf8392a907df0","observation_id":"c26d160b-1159-4e10-82c8-e2863e8bdd32","resolution":{"observed_at":"2026-08-05T13:07:12.886017Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.749737Z","title":"Llm-sentry: A model-agnostic human-in-the-loop framework for securing large language models,","venue":null,"work_id":"f634e208-19ed-4bb6-b616-2c68a9a3e90d","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.113475Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:e231a023164d31bdaa45cd9f82f15a85adcebaee1f431781a87faca5a1cd77c3","observation_id":"b1ca3fc5-ae11-4d66-9915-0d7210cf403a","resolution":{"observed_at":"2026-08-05T13:07:12.791201Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.658893Z","title":"Data stealing attacks against large language models via backdooring,","venue":null,"work_id":"46216b1d-bd1a-459a-ad68-efeab630df24","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.163435Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:00fc76a44f974866e4d32d4cb89633cac4603a4ccbc293decce98ac4399d4ba4","observation_id":"ac480b85-72b1-44da-9fa0-da38193ba19d","resolution":{"observed_at":"2026-08-05T13:07:12.699241Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.553196Z","title":"Efficient llm jailbreak via adaptive dense-to-sparse constrained optimization,","venue":null,"work_id":"62b08782-c797-45cf-9c1c-c50e4459560c","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.258365Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:decfc6b73327cb8d1a60caf6829a237b3d6f87ae88e0543f58968dc80bdd9b74","observation_id":"11be3464-c764-458e-aa99-a246e1ae73da","resolution":{"observed_at":"2026-08-05T13:07:12.601125Z","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":"2408.04686","last_updated":"2024-08-08T09:18:47Z","snapshot_observed_at":"2026-08-09T04:54:31.022151Z","submitted_at":"2024-08-08T09:18:47Z","title":"Multi-Turn Context Jailbreak Attack on Large Language Models From First Principles","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.04686","snapshot_observed_at":"2026-08-05T13:07:11.356493Z","title":"Multi-turn context jailbreak attack on large language models from first principles,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.356493Z"},"links":{"cited_paper":"/paper/2408.04686","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:5c1be039d0674ffd06497c40c382cbc47156c7a4b31ce9d674c66b74c26efd8a","observation_id":"e0f1fab5-0a0c-4458-ad74-375c31f3b84b","resolution":{"observed_at":"2026-08-05T13:07:11.356493Z","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":"2026-08-05T13:07:12.464916Z","title":"Harmbench: A standardized evaluation framework for automated red teaming and robust refusal,","venue":null,"work_id":"388c08fb-e495-4101-ab2b-dbc029e4a20f","year":2024},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.419406Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:ef522bd4b867fb69cafd6836e83dd2b99b6bb8f20307959e4c354cbc3241c8a0","observation_id":"eb265e30-d24b-4fc2-9a06-d68ceda36942","resolution":{"observed_at":"2026-08-05T13:07:12.501654Z","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":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-05T13:07:11.460521Z","title":"Distilling the knowledge in a neural network,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.460521Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:338a30437dc2e89ba9d4a016b085a77071517a61fcc321624de125928a6c1d44","observation_id":"328185fa-71cd-47d5-b072-c4de987f9897","resolution":{"observed_at":"2026-08-05T13:07:11.460521Z","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":"2026-08-05T13:07:12.375630Z","title":"Wikitext-2 data,","venue":null,"work_id":"38a075a9-3363-4fc2-a163-68f0cc85c8e2","year":2022},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.522660Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:99501156f9fc0bda19c76dddb4cd8d8445fd1113a17bb7b875f10d153028fc7a","observation_id":"e979c1f7-5401-4ea3-84d4-ebd2145ec30c","resolution":{"observed_at":"2026-08-05T13:07:12.413599Z","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T13:07:12.245000Z","title":"Wikitext103,","venue":null,"work_id":"436158ff-a6f4-4a98-84d9-9cc7fded7a07","year":2022},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.581925Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:2fa2a1eba52841413c0649e6c21e426129e593d3388b45e726ce0e2ce120b788","observation_id":"2f9b11fa-484e-4ba5-af49-a60c3a682def","resolution":{"observed_at":"2026-08-05T13:07:12.288411Z","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":"2311.17035","last_updated":"2023-11-28T18:47:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-28T18:47:03Z","title":"Scalable Extraction of Training Data from (Production) Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17035","snapshot_observed_at":"2026-08-05T13:07:11.611656Z","title":"Scalable extraction of training data from (production) language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.611656Z"},"links":{"cited_paper":"/paper/2311.17035","citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:727d277485bdcdb4fe4f58c488483c6e7f8b9e3af72f81a10f4e73636a241306","observation_id":"ce7c9430-08b1-4459-bfee-fd9fcdbdbf39","resolution":{"observed_at":"2026-08-05T13:07:11.611656Z","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":"2026-08-05T13:07:12.144775Z","title":"Quantile-based cumulative kullback-leibler divergence in past lifetime: Some properties and applications,","venue":null,"work_id":"3fa1e4dc-45bb-46ab-aee5-ec27943af58b","year":2025},"citing_paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T13:07:11.652209Z"},"links":{"citing_paper":"/paper/2509.00973"},"observation_digest":"sha256:42aca935447d450b66db470614a50d17ae89474de78674d3ecbbce6afb900a11","observation_id":"b5c11fab-6d5f-4263-b1fc-cdcfa188b7aa","resolution":{"observed_at":"2026-08-05T13:07:12.192698Z","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"}}],"paper":{"arxiv_id":"2509.00973","last_updated":"2025-08-31T19:38:24Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-08T16:33:01.329997Z","submitted_at":"2025-08-31T19:38:24Z","title":"Clone What You Can't Steal: Black-Box LLM Replication via Logit Leakage and Distillation"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":16},"total_outbound_references":23},"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 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2509.00973."}