{"as_of":"2026-08-13T03:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7eb25b360bdcdac9e4380dc196be59bab694f061f56df670464680344f45d873","coverage":[{"denominator":26,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":26,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T20:47:45.786448Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2509.10561/citation-record","integrity":"/paper/2509.10561/integrity","json":"/paper/2509.10561/citation-record.json","paper":"/paper/2509.10561"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T20:47:45.620653Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.620653Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:7ac057e1c0f5c48902133c31bca6d3f7a6e041c9f81a33fbb65f6d3b764bc718","observation_id":"bcf6ed37-689f-4147-a3e5-c7e432f06786","resolution":{"observed_at":"2026-08-04T20:47:45.620653Z","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":"2026-08-04T20:47:46.510100Z","title":"Deep learning with differential privacy","venue":null,"work_id":"432c457e-7244-4415-b504-361ced73e16c","year":2016},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.629951Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:e06e7ca92979361ae2c7a27eb3c3237670ee3b77bdbed6c64563547f40417a79","observation_id":"4b1e56db-a72b-4969-bb21-b6beae81714c","resolution":{"observed_at":"2026-08-04T20:47:46.517131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11514","last_updated":"2024-07-30T23:37:20Z","snapshot_observed_at":"2026-08-10T22:25:06.219020Z","submitted_at":"2023-12-12T18:57:08Z","title":"LLM in a flash: Efficient Large Language Model Inference with Limited Memory","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11514","snapshot_observed_at":"2026-08-04T20:47:45.635928Z","title":"Llm in a flash: Efficient large language model inference with limited memory (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.635928Z"},"links":{"cited_paper":"/paper/2312.11514","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:046155eb36588d1e0723ca8bbba745ef64af0a9095b66aec0967c44fd0054307","observation_id":"7c460a86-acb3-40fa-85a6-8eafae05757b","resolution":{"observed_at":"2026-08-04T20:47:45.635928Z","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":"2026-08-04T20:47:46.489413Z","title":"Gptcache: An open-source semantic cache for llm applications enabling faster answers and cost savings","venue":null,"work_id":"c17f73f5-705e-475b-aba3-fc8e54d367e4","year":2023},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.645063Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:c85c292445105be10e06e8362cf3a47b877452c00255b901c05efee10b404699","observation_id":"eab1d099-78f0-4adc-b983-00efa4eb3c28","resolution":{"observed_at":"2026-08-04T20:47:46.494718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.466637Z","title":"Bulletproofs: Short proofs for confidential transactions and more","venue":null,"work_id":"4e03eccb-f5cf-4812-bda6-26c15914d259","year":2018},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.651787Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:cc918383c0aa57d7873db4da0dc17d9f2b877679ccac0ef52cb5d83a01d69261","observation_id":"902f7691-e93a-40c7-965a-fcf1cfae91a4","resolution":{"observed_at":"2026-08-04T20:47:46.472514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:45.657726Z","title":"The algorithmic foundations of differential privacy","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.657726Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:81387cf390e283de028b71c539daec57628870602bcd0a4874a1f6b0a9967198","observation_id":"f688c953-af81-4baa-86cb-7b93b82aee0a","resolution":{"observed_at":"2026-08-04T20:47:45.657726Z","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":"2026-08-04T20:47:46.432477Z","title":"Non-interactive verifiable computing: Outsourcing computation to untrusted workers","venue":null,"work_id":"0f945512-337d-412c-8896-3fc9f3758735","year":2010},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.662428Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:1c9bef1c9e132d276ee60aad069addb23713037729c77ac906613f3105545098","observation_id":"df69c91d-4662-4e4e-ab91-c2ba1988a15a","resolution":{"observed_at":"2026-08-04T20:47:46.437615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6572","last_updated":"2015-03-20T20:19:16Z","snapshot_observed_at":"2026-08-12T17:13:46.394331Z","submitted_at":"2014-12-20T01:17:12Z","title":"Explaining and Harnessing Adversarial Examples","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6572","snapshot_observed_at":"2026-08-04T20:47:45.668697Z","title":"Explaining and harnessing adversarial examples","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.668697Z"},"links":{"cited_paper":"/paper/1412.6572","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:5940cd9c6a96e2db5d8235c1a991923dfdb41bbaf3cdcdd26b508a7ac6fc1c3a","observation_id":"6be208be-2b01-4fd3-8ea8-1f4a03b8986d","resolution":{"observed_at":"2026-08-04T20:47:45.668697Z","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":"2026-08-04T20:47:46.413203Z","title":"N-sanitization: A semantic privacy-preserving framework for unstructured medical datasets","venue":null,"work_id":"78a2b9ff-cb45-4b57-b98f-02ff77b20fea","year":2020},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.675361Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:b0e7021fabb1647d65a244b8bc43c4a359520f525c4fcbf823f99e05986ba387","observation_id":"a1a9849a-7f7f-4d0c-9772-05fbc2a9e115","resolution":{"observed_at":"2026-08-04T20:47:46.419417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.387334Z","title":"Privacy-preserving federated learning for industrial edge computing via hybrid differential privacy and adaptive compression","venue":null,"work_id":"6a238e72-39fd-41f6-9214-293c5d7483eb","year":2021},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.681211Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:2a2b87f292cca42f03094719b4bef90b54cc5f4bcb51c1cd6a563ec9c0ae7844","observation_id":"41d0d597-41da-4084-8032-5f394f2dafcc","resolution":{"observed_at":"2026-08-04T20:47:46.395990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.367765Z","title":"Scalm: Towards semantic caching for automated chat services with large language models","venue":null,"work_id":"5c87ae20-fa47-4d78-a899-ddb06e635c15","year":2024},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.686972Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:fd12177615a813195337ecae09076257c142088239ffc370dc457a5a9b0307b3","observation_id":"20e9597c-3240-4da7-91c0-9c552d4e2988","resolution":{"observed_at":"2026-08-04T20:47:46.373342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.348247Z","title":"t-closeness: Privacy beyond k-anonymity and l-diversity","venue":null,"work_id":"f1eaeb5b-2222-4299-b519-316b8ed098b8","year":2007},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.696384Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:69ee808e2f3b33ac3d9fa4d48e53ddd65c50284464c49f5ddd4137ab52c4a9b6","observation_id":"5e2651e7-5a79-4db1-9c0a-893de8cb03c0","resolution":{"observed_at":"2026-08-04T20:47:46.353494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.329298Z","title":"l-diversity: Privacy beyond k-anonymity","venue":null,"work_id":"7fad047a-09eb-4d07-bb5a-16886aebe308","year":2007},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.701918Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:5341860d0065adf3d60f66ede86e6ac4202a6ecbacb3fc641455d49467e2ba51","observation_id":"0a936f28-1605-4d4b-9d2f-8fa5102e8423","resolution":{"observed_at":"2026-08-04T20:47:46.334834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.129616Z","title":"Anonymization techniques for privacy preserving data publishing: A comprehensive survey","venue":null,"work_id":"114f1ac8-d6c9-4281-95d3-fb7d444b2388","year":2020},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.707206Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:c99584295dbd53a0866b0d52ae8aeaa829d1fc2dafcdb1f818ffc65c495698ae","observation_id":"cb2777ce-111e-4920-9594-8c82d1d4748b","resolution":{"observed_at":"2026-08-04T20:47:46.136380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:45.713141Z","title":"Communication-efficient learning of deep networks from decentralized data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.713141Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:e09e302256cf3c29a63053559925913438feac8d6305a462d5ee58685e46ff91","observation_id":"ca05c2e4-f018-4605-8bbe-3c0bb002657e","resolution":{"observed_at":"2026-08-04T20:47:45.713141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10530","last_updated":"2019-08-28T03:03:25Z","snapshot_observed_at":"2026-08-07T03:15:48.518041Z","submitted_at":"2019-08-28T03:03:25Z","title":"R\\'enyi Differential Privacy of the Sampled Gaussian Mechanism","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10530","snapshot_observed_at":"2026-08-04T20:47:45.718288Z","title":"R 'enyi differential privacy of the sampled gaussian mechanism","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.718288Z"},"links":{"cited_paper":"/paper/1908.10530","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:9622e60a5feef04ec556fe1ac11399dc67360263b25a4e9737eff851b32e5a12","observation_id":"181e9df7-b50b-4485-b254-eb204d3c396d","resolution":{"observed_at":"2026-08-04T20:47:45.718288Z","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":"2026-08-04T20:47:46.089443Z","title":"Pinocchio: Nearly practical verifiable computation","venue":null,"work_id":"315988d9-7bbe-4969-a0ac-e16b736fb856","year":2016},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.723885Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:85df6229379d0ae009ddfb042e7af86c52f4c1b70004711d4b9f0d664a60f726","observation_id":"5a6b470c-035c-44b6-b1c5-4a2ce5c5d43c","resolution":{"observed_at":"2026-08-04T20:47:46.097175Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18535","last_updated":"2026-03-29T15:59:38Z","snapshot_observed_at":"2026-08-09T20:22:47.797639Z","submitted_at":"2025-02-25T05:04:27Z","title":"A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.18535","snapshot_observed_at":"2026-08-04T20:47:45.729292Z","title":"A survey of zero-knowledge proof based verifiable machine learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.729292Z"},"links":{"cited_paper":"/paper/2502.18535","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:8cc277f739f07ebb76cace79a7198d67ec9b00d443b6e3ac56927fed77b4b894","observation_id":"599784d8-b9ff-479b-972e-8083db79dfe7","resolution":{"observed_at":"2026-08-04T20:47:45.729292Z","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":"2026-08-04T20:47:46.066789Z","title":"Privacy odometers and filters: Pay-as-you-go composition","venue":null,"work_id":"8a6811fb-8d64-48f1-8c2f-1757e2c24ab5","year":2016},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.737054Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:183d61c0a581c2a389fdb44efa7c080d31e3c8c460828d0a0e55e09a4bef880b","observation_id":"98c263fa-4e49-4484-a65a-5ab558c4ad4c","resolution":{"observed_at":"2026-08-04T20:47:46.074605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.044687Z","title":"k-anonymity: A model for protecting privacy","venue":null,"work_id":"ede0d8c8-1b27-4275-852f-c8d21219efec","year":2002},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.743277Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:af278a546683ae0e30dda6d5ac786d97c0ec3d8340befefc16c92162db4bf6a0","observation_id":"22582fae-0bda-4d69-9af1-63043b57a3fe","resolution":{"observed_at":"2026-08-04T20:47:46.050914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-04T20:47:46.023663Z","title":"Attention is all you need","venue":null,"work_id":"1325a295-b17f-454f-a00b-a6241c5aa76e","year":2017},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.751735Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:74824f210ecf1897743506d8c578e9bc566dd85ca2f1ac3917fa95e63ff87e88","observation_id":"ee6c0384-31a7-4aec-8719-418c1cbf8bc8","resolution":{"observed_at":"2026-08-04T20:47:46.031614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16291","last_updated":"2023-10-19T16:27:03Z","snapshot_observed_at":"2026-08-11T16:01:36.938012Z","submitted_at":"2023-05-25T17:46:38Z","title":"Voyager: An Open-Ended Embodied Agent with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16291","snapshot_observed_at":"2026-08-04T20:47:45.758279Z","title":"Voyager: An open-ended embodied agent with large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.758279Z"},"links":{"cited_paper":"/paper/2305.16291","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:8ff4b68950cd7a8e20d9c32cc2a4ffd63a92d62d0c6d155a92ed55c3823cbd51","observation_id":"cf5e22ee-1ee7-4cc5-9833-55fb7473f4ed","resolution":{"observed_at":"2026-08-04T20:47:45.758279Z","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":"2026-08-04T20:47:45.767760Z","title":"A survey on large language model based autonomous agents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.767760Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:33356bd2c7fc831c5134e03a660b0c7396138ea9d9d46fdd2273617723c5a38b","observation_id":"7f7093bc-ee39-451b-a341-5d817b70cb25","resolution":{"observed_at":"2026-08-04T20:47:45.767760Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00088","last_updated":"2024-09-14T04:01:09Z","snapshot_observed_at":"2026-08-12T22:57:42.454673Z","submitted_at":"2024-08-26T03:33:36Z","title":"On-Device Language Models: A Comprehensive Review","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.00088","snapshot_observed_at":"2026-08-04T20:47:45.773840Z","title":"On-device language models: A comprehensive review","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.773840Z"},"links":{"cited_paper":"/paper/2409.00088","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:c74a25598d1e08c5edccdd26c606be1d830aaa35815795386333a94fedc78098","observation_id":"563cd81c-8614-4883-a62c-3d1f055f82b6","resolution":{"observed_at":"2026-08-04T20:47:45.773840Z","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":"2026-08-04T20:47:45.780240Z","title":"React: Synergizing reasoning and acting in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.780240Z"},"links":{"citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:49e1d70f7e334a194ca145145c21cbc19276e53fb97bde7efc3ceed1a61d3b27","observation_id":"32bea0db-4076-49dc-b8be-e66fcc181e5e","resolution":{"observed_at":"2026-08-04T20:47:45.780240Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.00753","last_updated":"2026-05-06T06:53:19Z","snapshot_observed_at":"2026-07-06T21:17:42.853055Z","submitted_at":"2025-05-01T08:29:26Z","title":"LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.00753","snapshot_observed_at":"2026-08-04T20:47:45.786448Z","title":"A survey on large language model based human-agent systems","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-04T20:47:45.786448Z"},"links":{"cited_paper":"/paper/2505.00753","citing_paper":"/paper/2509.10561"},"observation_digest":"sha256:702347937db387f945521a50e52adeea09577a7957a60993f0756ee8d27931f7","observation_id":"27ebe5d9-4bf0-4202-8a37-4de5cbcd9590","resolution":{"observed_at":"2026-08-04T20:47:45.786448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.10561","last_updated":"2025-09-10T07:59:01Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-11T18:43:50.567663Z","submitted_at":"2025-09-10T07:59:01Z","title":"AVEC: Bootstrapping Privacy for Local LLMs"},"reference_resolution":{"displayed":26,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":14},"total_outbound_references":26},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2509.10561."}