{"as_of":"2026-08-07T11:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2e3636920398565bb129cbc96ef65bc61be4b4c15ee0eb0eb3364fa504afed72","coverage":[{"denominator":89,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":89,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:18:32.938601Z","state":"measured"},{"denominator":90,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":90,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T02:28:36.749900Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.16872","snapshot_observed_at":"2026-08-01T02:28:36.749900Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25451","last_updated":"2026-07-28T08:41:31Z","snapshot_observed_at":"2026-08-05T00:48:38.387718Z","submitted_at":"2026-07-28T08:41:31Z","title":"Bits and Memories: Measuring Verbatim Extraction Across LLM Quantization","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-01T02:28:36.749900Z"},"links":{"cited_paper":"/paper/2507.16872","citing_paper":"/paper/2607.25451"},"observation_digest":"sha256:3259bd5230ef1870e6e1543cbe461459bfe4fbcaa514189c6ebae92f50212696","observation_id":"fc02a45e-ab91-4dc6-a180-a48b3ea83203","resolution":{"observed_at":"2026-08-01T02:28:36.749900Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.16872/citation-record","integrity":"/paper/2507.16872/integrity","json":"/paper/2507.16872/citation-record.json","paper":"/paper/2507.16872"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:18:21.096242Z","title":"Deep learning based caching for self-driving cars in multi-access edge com- puting,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.096242Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:213c92fdb932753959cf0ecf80c2f602eb63151eecd3d0f9f6446dafbd2b60c4","observation_id":"c3d9d630-6dd0-4104-837a-0d0d748a8c9e","resolution":{"observed_at":"2026-08-06T15:18:21.096242Z","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":"2026-08-06T15:18:21.362905Z","title":"Highly accurate protein structure prediction with alphafold,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.362905Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3b4822c13335b3cc3096f8fb96c7f360b20e1929a7f5ba2972fdadaf51b90d09","observation_id":"16e5fbbf-f254-494c-a755-6331a3133267","resolution":{"observed_at":"2026-08-06T15:18:21.362905Z","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":"2026-08-06T15:18:21.465768Z","title":"What chatgpt and generative ai mean for science,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.465768Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:e974901b2356da0b774408083feb087f89ed704cbf8b2fd8a968a46bd062cbbc","observation_id":"49823777-5c81-439c-ab94-f0c2cf3e1faa","resolution":{"observed_at":"2026-08-06T15:18:21.465768Z","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":"2026-08-06T15:18:21.581646Z","title":"Diffusion models: A comprehensive survey of methods and applications,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.581646Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:78444ca5725c876ddc57c738a9e21a54756d5774bed23766a636feac54798334","observation_id":"f03b22bd-05d5-49d4-91c9-7f20dd49a6a8","resolution":{"observed_at":"2026-08-06T15:18:21.581646Z","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":"2026-08-06T15:18:21.739540Z","title":"Model compression and acceleration for deep neural networks: The principles, progress, and challenges,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.739540Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:5d19452f8ad28875d666c71fb9848e15f1da4b079de3cb0d60ce78071c8b1e26","observation_id":"8718efe8-205b-4407-9ebb-935982bb3bb0","resolution":{"observed_at":"2026-08-06T15:18:21.739540Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1510.00149","last_updated":"2016-02-15T06:25:40Z","snapshot_observed_at":"2026-08-04T16:59:47.843960Z","submitted_at":"2015-10-01T09:03:44Z","title":"Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1510.00149","snapshot_observed_at":"2026-08-06T15:18:21.847001Z","title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.847001Z"},"links":{"cited_paper":"/paper/1510.00149","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:c2ddb765f65cae6e332f7209c4e86384f867abb3950de4ad14e73b3d4f5322ce","observation_id":"51dae251-14ad-4f18-98b3-f20722b2e651","resolution":{"observed_at":"2026-08-06T15:18:21.847001Z","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":"2026-08-06T15:18:21.957163Z","title":"A com- prehensive survey on model compression and acceleration,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:21.957163Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:9f47747c8c6016dd495aee7afdc87220690e06640aa9884844fff83f0d8d906e","observation_id":"a5a14d3c-91f1-498b-8e99-7836c907e4fc","resolution":{"observed_at":"2026-08-06T15:18:21.957163Z","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":"2026-08-06T15:18:22.119025Z","title":"Sparse double descent: Where network pruning aggravates overfitting,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:22.119025Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:0af83ae8e1afbb0228bc37cc893116e5f32086fd5cb3aa7393437cbfbba70362","observation_id":"96e16c02-1bcb-4908-b1de-06d6bd342f75","resolution":{"observed_at":"2026-08-06T15:18:22.119025Z","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":"2026-08-06T15:18:22.342560Z","title":"Spar- sity in deep learning: Pruning and growth for efficient inference and training in neural networks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:22.342560Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:9eb357bea5b3448dbcf68ce4f7e36cc0efb430dc5463abcb1c163a1f87281227","observation_id":"357eea9f-4733-4f13-acda-e15a6b53b615","resolution":{"observed_at":"2026-08-06T15:18:22.342560Z","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":"2026-08-06T15:18:22.536693Z","title":"Variational dropout spar- sifies deep neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:22.536693Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a1f1a9358353dbf0c3f6b0675f4bfa45307004209832a06bfd9a97fa77d98822","observation_id":"e057dae1-2ca5-4973-a0a4-9c1e4b74c079","resolution":{"observed_at":"2026-08-06T15:18:22.536693Z","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":"2026-08-06T15:18:48.199463Z","title":"A survey on model com- pression for large language models,","venue":null,"work_id":"ad58f2ba-2b21-4e26-aacd-864310834539","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:22.652651Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:b2169a075c9b1f1db4be1f7c89431556e436000260bdb8a6b9db9ad12a62bfe6","observation_id":"c00cf94b-8dbe-4142-8ca3-fd8c9868e41a","resolution":{"observed_at":"2026-08-06T15:18:48.289566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:47.864027Z","title":"Quantization backdoors to deep learning commercial frameworks,","venue":null,"work_id":"9eaf58f2-5451-48f6-a9df-36577d43055d","year":2023},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:22.842344Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:b5691e1b9b08fbcf436e9bb953d7a9691141851249cfc1c25a45f9e12aa7c437","observation_id":"c03bc318-aa5a-4fdf-92e7-241c4052dfa6","resolution":{"observed_at":"2026-08-06T15:18:48.059143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.11942","last_updated":"2020-02-09T03:00:18Z","snapshot_observed_at":"2026-07-06T08:24:44.631342Z","submitted_at":"2019-09-26T07:06:13Z","title":"ALBERT: A Lite BERT for Self-supervised Learning of Language Representations","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.11942","snapshot_observed_at":"2026-08-06T15:18:23.037839Z","title":"Albert: A lite bert for self-supervised learning of language represen- tations,","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.037839Z"},"links":{"cited_paper":"/paper/1909.11942","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:cee64a9a7b72824fabe71a0afaa54811b454de00d4392a44a70619126381dcec","observation_id":"e30bf0e9-fa7d-4841-aa2b-1b8b77b76c9b","resolution":{"observed_at":"2026-08-06T15:18:23.037839Z","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":"2026-08-06T15:18:47.591755Z","title":"Loraprune: Structured pruning meets low-rank parameter-efficient fine-tuning,","venue":null,"work_id":"78a9895e-8b54-48d5-b345-00b63f360eaa","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.184420Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:bb29bbe061d5ffd3b8e50151db349c3c2e7046988c10f1b5a62b07a368f0fcf2","observation_id":"71977555-a415-439d-9c63-f514d4fc642d","resolution":{"observed_at":"2026-08-06T15:18:47.707506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:47.391558Z","title":"Q8bert: Quan- tized 8bit bert,","venue":null,"work_id":"40f59cdd-5cf1-40cd-abdc-63c6436e162b","year":2019},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.313920Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:ba6c675c94c9b99e4e2ef59636d0877b5c8974148ceb09120c621ac1e4e1e436","observation_id":"538c577c-6f5a-4bdb-85c0-527fe0a5f004","resolution":{"observed_at":"2026-08-06T15:18:47.451251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:47.152181Z","title":"Atom: Low-bit quanti- zation for efficient and accurate llm serving,","venue":null,"work_id":"6dbc2d6d-925d-4362-8b20-c66857eaa906","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.424949Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:872816a53db512945589f3b7e2b13722aeb40c531a6bd03f97b6979d9a16b7ff","observation_id":"4c0f6ae5-4da0-4160-8a68-e2546801e35f","resolution":{"observed_at":"2026-08-06T15:18:47.252089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:46.957056Z","title":"Exploiting llm quantization,","venue":null,"work_id":"d42c1d61-a086-49c0-966a-07bacdb3496e","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.555944Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:760b86fb821e8ab4321da755b30572e8de4cf0a831c20fc54dd6930e6b02c444","observation_id":"bd7f2614-7c57-4c94-87cf-89b18ac7f135","resolution":{"observed_at":"2026-08-06T15:18:47.021207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:46.779332Z","title":"Auditing membership leakages of multi-exit networks,","venue":null,"work_id":"7440cb74-7a00-4c0d-93f1-22e4d371b746","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.666621Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3ca2a60e56db6ae7c34259c521ebe0c4808740114f2935771d879f6160d1d3e1","observation_id":"e6e3e0c2-656b-4eb7-b580-78d34b73fcc6","resolution":{"observed_at":"2026-08-06T15:18:46.841058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:46.582757Z","title":"Member- ship inference attacks and generalization: A causal perspective,","venue":null,"work_id":"dffd0301-2f8d-4962-816c-f7d135fc495d","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.772306Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:449ef3953f1222cb80c954f28b0eac77b1f1123943603e428783a0f6804695bb","observation_id":"1396119b-7880-44ef-b0b3-6068126b75cc","resolution":{"observed_at":"2026-08-06T15:18:46.693215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:46.431485Z","title":"Enhanced membership inference attacks against machine learning models,","venue":null,"work_id":"36a17831-d3af-4f0e-a2e2-f52af6200bad","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:23.940936Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3ee531c6d5d0b7109295ee979746fd363df56f85cea0d5f6039041ca0db6ea4b","observation_id":"e26a4249-8efb-4691-9bea-c12c70fad979","resolution":{"observed_at":"2026-08-06T15:18:46.510216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:46.309602Z","title":"Membership inference attacks and defenses in classification models,","venue":null,"work_id":"a38f167d-0ed7-4d76-980b-5a0148720098","year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.074750Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:33a083fa9dda221a99ec49d60ed1f069c4558ef101b71c1f74eb689115f72591","observation_id":"6186b8e8-cadf-4da3-8705-935e6bc5505c","resolution":{"observed_at":"2026-08-06T15:18:46.366309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:24.209438Z","title":"Membership inference attacks against machine learning models,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.209438Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:74628f7d4cd3ee256230dc547c003fa0fd337e3cf7c8de75e5176410f83d2c8b","observation_id":"361d6386-e1fc-4e41-83ba-2d4f0ff8c8c2","resolution":{"observed_at":"2026-08-06T15:18:24.209438Z","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":"2026-08-06T15:18:46.095150Z","title":"Membership inference attacks from first principles,","venue":null,"work_id":"b68a34c9-3fb5-4a1a-9a3c-d1f6eb4758fd","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.315644Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a641b88acfc1deaa402de114ce0f63e9e40995ffc4a2f16202b6cee1fcf23b8c","observation_id":"b3bd642d-56c7-4866-9539-f1ff22a391fd","resolution":{"observed_at":"2026-08-06T15:18:46.199757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:45.965476Z","title":"Seqmia: Sequential-metric based membership inference attack,","venue":null,"work_id":"c3634990-1c24-495b-9ccf-b0f0e990420d","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.368754Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:35cf87d50384999a4dd1200928388ae5e547c5c471e3af24b4815dfd569494ca","observation_id":"da711e6f-fbf9-4555-9cb8-614bb1f7bf18","resolution":{"observed_at":"2026-08-06T15:18:46.025527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:45.742650Z","title":"Is difficulty calibration all we need? towards more practical membership inference attacks,","venue":null,"work_id":"f7e5d8ce-0d73-48a1-bc01-1aad48a4f19e","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.497023Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:412af539e0b8836866854106893c28c0778fd4e8e12f9f5f7284326dafdc8213","observation_id":"623765f2-6888-498f-88f2-99c027b4b234","resolution":{"observed_at":"2026-08-06T15:18:45.857001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:45.525313Z","title":"Gan-leaks: A taxonomy of membership inference attacks against generative models,","venue":null,"work_id":"2ef067d0-5d31-4cc9-a81d-170eff035743","year":2020},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.572390Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:afc6db54e432ef47168551af03ad26521eba68b82ca5c76d3312b4aa5fdab6b5","observation_id":"049f2b71-bc98-42d7-a662-c33b5f8e8fe8","resolution":{"observed_at":"2026-08-06T15:18:45.612468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:45.339071Z","title":null,"venue":null,"work_id":"ffb33acf-583f-4207-a806-595935c4fc20","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.661883Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a54f8fa913226789c275a2ff4c536213ecd85a952cf0da46a472f5b35e8e2950","observation_id":"f2024b30-b662-4bf7-b38e-fbc7a913504b","resolution":{"observed_at":"2026-08-06T15:18:45.437082Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:24.799977Z","title":"Membership inference attacks and defenses in neural network pruning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.799977Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:0a3d72a9505884720d4f0bbcbc3e30778c4fde804efa4c8bac366c8c07b85d5a","observation_id":"bb19e2a8-603a-4155-b207-8d596aeb2139","resolution":{"observed_at":"2026-08-06T15:18:24.799977Z","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":"2026-08-06T15:18:45.239619Z","title":"Machine learning with membership privacy using adversarial regularization,","venue":null,"work_id":"c6bbcc60-6597-46ed-8429-f1d4307bd137","year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:24.913808Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:74c66f451236137fb819afb7cce1566fb28767c1a68ecd7d51ae5839ce5e6307","observation_id":"034297f7-fc5d-4b27-9291-10d81761d6db","resolution":{"observed_at":"2026-08-06T15:18:45.278356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:45.099956Z","title":"Systematic evaluation of privacy risks of machine learning models,","venue":null,"work_id":"2e06b3a0-e58d-4aa0-990d-06ee485c3e85","year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.034685Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:45433fc68e09c25d6bbe0ed40802fafcb31f481e7a7d3065267620a04325f7e6","observation_id":"2d940c20-19fa-4844-a11a-4004f3e13508","resolution":{"observed_at":"2026-08-06T15:18:45.178828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:25.208390Z","title":"Privacy risk in machine learning: Analyzing the connection to overfitting,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.208390Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:96252614b5d198b2f809a10f6ddea5ba896ede16a7153e3bacf1306b93b753c3","observation_id":"867248fa-2b83-479b-8b94-7e1afd1c7acd","resolution":{"observed_at":"2026-08-06T15:18:25.208390Z","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":"2026-08-06T15:18:44.799577Z","title":"Against membership inference attack: Pruning is all you need,","venue":null,"work_id":"4017a2c8-00fd-43ce-b381-8b2c07cca281","year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.309464Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:9b88a4b6f121fd1985a2b429e80770aec982c6fdac6f708e1b53602092d4adc5","observation_id":"18cfc604-d6ec-41cd-80e0-99d03faec7a0","resolution":{"observed_at":"2026-08-06T15:18:44.930521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-06T15:18:25.411591Z","title":"Llama: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.411591Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:b9c533d1356c55a4c5762910b38e9f588eec23f59429540d54000c3b797312fe","observation_id":"9de7d6e1-90ed-45f1-b2ba-a94bb4a2d45b","resolution":{"observed_at":"2026-08-06T15:18:25.411591Z","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":"2026-08-06T15:18:44.512380Z","title":null,"venue":null,"work_id":"d540a455-78cb-4e1e-9312-8d9ec90e6663","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.541676Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:b1d427ebef0b4edad62fdb70289e85ec560ad4920a447665b91a7b643b98dd4b","observation_id":"7d633ba0-1ac1-44ee-a7d0-fa19b6ebb4dc","resolution":{"observed_at":"2026-08-06T15:18:44.623557Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:44.284659Z","title":"Quantization and training of neural networks for efficient integer-arithmetic-only inference,","venue":null,"work_id":"c2a567f4-eb00-48c3-94c3-9b9b0e2ff53d","year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.642744Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:0bce1214d457707782373d9158b6e9228f0baee7e0ab4506041a7154f56b9fdc","observation_id":"519fd57a-9913-4a68-acc1-65796dfb89b1","resolution":{"observed_at":"2026-08-06T15:18:44.383569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:44.071610Z","title":"Structured pruning of deep con- volutional neural networks,","venue":null,"work_id":"24bc63a7-dc2c-4283-8961-de38674887a4","year":2017},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.768980Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a12030fd85ed927884bd20e4a5e1d1f84a2bba3d7ad4acf9b7c87782a524c570","observation_id":"359cb8b5-5c3b-4bf6-b026-7bebc4cb61fa","resolution":{"observed_at":"2026-08-06T15:18:44.198812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:43.806752Z","title":"A survey of quantization methods for efficient neural network inference,","venue":null,"work_id":"642ecc42-b436-4a17-b8cb-67409068f0e9","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:25.908658Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:cffd05189874290d422bb9ad7afc8cdbabb9626ef6750e257d1fa53f5b78f728","observation_id":"fe44c792-9650-4824-b913-6d6c4bdde90b","resolution":{"observed_at":"2026-08-06T15:18:43.922716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:43.559932Z","title":"Quantization networks,","venue":null,"work_id":"5367a3dd-0852-4452-93cb-26e5d6f59704","year":2019},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.111883Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:78f7ff965d7dad6d03e96aa9e20ed931cd7bc12f525cd175dc13b3a7c6c4c2ce","observation_id":"df979d41-5d21-47bd-a7d0-8b4b69f0c209","resolution":{"observed_at":"2026-08-06T15:18:43.681204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.08710","last_updated":"2017-03-10T17:57:56Z","snapshot_observed_at":"2026-07-06T05:08:42.861486Z","submitted_at":"2016-08-31T02:29:59Z","title":"Pruning Filters for Efficient ConvNets","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.08710","snapshot_observed_at":"2026-08-06T15:18:26.229570Z","title":"Pruning filters for efficient convnets,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.229570Z"},"links":{"cited_paper":"/paper/1608.08710","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:cee4c11345290213d736606409c88eb1d90d64a7a2e7b63f057ddbfd11e9de0a","observation_id":"338e2344-d5da-44ae-bef1-016aade63bdd","resolution":{"observed_at":"2026-08-06T15:18:26.229570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03853","last_updated":"2024-10-11T09:43:32Z","snapshot_observed_at":"2026-08-03T01:48:18.654934Z","submitted_at":"2024-03-06T17:04:18Z","title":"ShortGPT: Layers in Large Language Models are More Redundant Than You Expect","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03853","snapshot_observed_at":"2026-08-06T15:18:26.479421Z","title":"Shortgpt: Layers in large language models are more redundant than you expect,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.479421Z"},"links":{"cited_paper":"/paper/2403.03853","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:450708eba46133ee10d1b109b1d008fa2cd81eb8248a4493139c7d082272c157","observation_id":"7aea0721-329e-4bbf-a1ac-3e419f4a82a4","resolution":{"observed_at":"2026-08-06T15:18:26.479421Z","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":"2026-08-06T15:18:43.119237Z","title":"Accurate post training quantization with small calibration sets,","venue":null,"work_id":"5c969bdc-2f86-49e5-8620-e2e7e1a1fa5b","year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.548919Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:d59125d9a9e6640f4daac8039a90e1b96705c8b48da3d1d06e52945919f79b1f","observation_id":"ec047fdc-efec-461c-8bbe-5463bd7f4b26","resolution":{"observed_at":"2026-08-06T15:18:43.266337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:42.873588Z","title":"Analyzing inference privacy risks through gradients in machine learning,","venue":null,"work_id":"3c2a3601-9862-442a-8c54-6fe5d6ecd541","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.675921Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:ef0334b3277d79ff3d40c969502ce3a7943af2ecc1fa2695229fda7e3744a8cc","observation_id":"a6c0a5db-6458-46b8-9948-56589d18b842","resolution":{"observed_at":"2026-08-06T15:18:43.008194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:42.643752Z","title":"Mitigating membership inference attacks by {Self-Distillation} through a novel ensemble architecture,","venue":null,"work_id":"85e96feb-8d68-40d8-9885-ba38634ca396","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.790772Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:864f976ecd8ae549d9e7121bf0395bfd19f8d8b87ccbf3c67133d97d5b9635a3","observation_id":"cd8a30f8-b76b-4635-8a37-223807a56e84","resolution":{"observed_at":"2026-08-06T15:18:42.743174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:42.450699Z","title":"Defending against membership inference attacks on iteratively pruned deep neural networks,","venue":null,"work_id":"11fe18b6-b1ab-4c98-960e-65c0b7d7a9ef","year":2025},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.905765Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:959315b4595f82a9efbc0f60656037d2543efd268389b3dc31581b77f9bb8311","observation_id":"a233bd19-36f1-43c4-84f4-1de1e4e1bf5a","resolution":{"observed_at":"2026-08-06T15:18:42.537098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.01246","last_updated":"2018-12-14T19:39:43Z","snapshot_observed_at":"2026-07-06T06:42:52.124532Z","submitted_at":"2018-06-04T17:38:42Z","title":"ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.01246","snapshot_observed_at":"2026-08-06T15:18:26.990706Z","title":"Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.990706Z"},"links":{"cited_paper":"/paper/1806.01246","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a2f074071be4f81d5e116d64f31b54569d38e9b57a23527b19d93983c53f3e53","observation_id":"7182ad9c-bf31-4755-a5ef-d85a4a2898f9","resolution":{"observed_at":"2026-08-06T15:18:26.990706Z","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":"2026-08-06T15:18:42.230354Z","title":"Please tell me more: Privacy impact of explainability through the lens of membership inference attack,","venue":null,"work_id":"31600b56-092d-463a-940a-2bfdcd52931e","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.054541Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:108b4df3362667948b0474069d297fc40ea02b6c499ee9d3a7d01405b3e16d6c","observation_id":"25a4411e-2cfb-4256-ad23-5592dd80e493","resolution":{"observed_at":"2026-08-06T15:18:42.343591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:41.987187Z","title":"Does training with synthetic data truly protect privacy?","venue":null,"work_id":"28751eae-0e11-4936-8b11-e2387966177c","year":2025},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.213789Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:2237735c5af18124d1f1a4f0674fb6bf2f7bd429fbe4361443e799c477fba60b","observation_id":"ca56b212-3fbe-4068-9b96-179e949b65a8","resolution":{"observed_at":"2026-08-06T15:18:42.097353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:27.336355Z","title":"When machine unlearning jeopardizes privacy,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.336355Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:99fd7206890569d2fb16ec6613f3aad7417caa53fb56fc70ad18120de3a62cfb","observation_id":"8ff18b66-184c-42da-9de5-6f8337ff594b","resolution":{"observed_at":"2026-08-06T15:18:27.336355Z","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":"2026-08-06T15:18:41.731417Z","title":"A unified membership inference method for visual self-supervised encoder via part-aware capability,","venue":null,"work_id":"2433c5ca-d556-4a0d-999c-de621599cf2a","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.492415Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:2bca13615b042331eb602709486092bf766063d5c2e9286cae8b463bd8e13ed0","observation_id":"b15c6e30-b18c-472a-bce3-dc606b2ac4c5","resolution":{"observed_at":"2026-08-06T15:18:41.842091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:41.497457Z","title":"SLMIA-SR: speaker-level member- ship inference attacks against speaker recognition systems,","venue":null,"work_id":"f58214ea-b529-4db5-b068-a86fea6987b6","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.607006Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:d3e79dcf9f30681f6854539468738d4e01f650ffbe22aea888a8938ae33ff6fc","observation_id":"133fc801-08e2-4032-b970-750c4f88d6d4","resolution":{"observed_at":"2026-08-06T15:18:41.612789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:41.258288Z","title":"Querychee- tah: Fast automated discovery of attribute inference attacks against query-based systems,","venue":null,"work_id":"96ca3566-5e13-434d-be41-d61c6fdc6508","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.712947Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:b3c4ba886d9f46faf29ae076cb7f8365891c0c933e7800cb730e2782161f8791","observation_id":"d982a247-be98-47c9-a9ed-0c663f83cb6b","resolution":{"observed_at":"2026-08-06T15:18:41.397779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:41.006587Z","title":"Diffence: Fencing mem- bership privacy with diffusion models,","venue":null,"work_id":"827ea644-d2d4-45c9-87c1-09141796b720","year":2025},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.859731Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:af78042f4342166b0b1022c8424adbc8dc9e567dd058bcf678c13abb8c09d8c7","observation_id":"55126610-24e9-4430-a1c2-596a4971818a","resolution":{"observed_at":"2026-08-06T15:18:41.112868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:40.724908Z","title":"Black-box membership inference attacks against fine-tuned diffusion models,","venue":null,"work_id":"efb2119a-b057-4174-889b-31db26b61416","year":2025},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:27.926417Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:42f537f4fbe9ce4b012e6861814fb999e80eb020518ba09486a48346b7714fc1","observation_id":"7b10c261-a274-49f4-be96-ca633ac86ec0","resolution":{"observed_at":"2026-08-06T15:18:40.876838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:40.418981Z","title":"Did the neurons read your book? document-level membership inference for large language models,","venue":null,"work_id":"737723d3-a262-4437-be46-667e0008232f","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.068692Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3ebe4aab745ee8ad2e4cef4a347af1b79df051f0edcb20ee42af47e21279df9a","observation_id":"b6b989f0-2144-4f10-a84c-0649a4c1d894","resolution":{"observed_at":"2026-08-06T15:18:40.555886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:40.185802Z","title":"Membership inference attacks against in-context learning,","venue":null,"work_id":"f9f6ca15-aa45-4316-939f-d1b4fa5fd5a4","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.162017Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:d819694f8aa4f9e2b513c7226a772b14b3a00233bfdcebe7d2cdd3be8c500edf","observation_id":"71b157a2-ef0b-4300-b2b8-d3dc69f883e4","resolution":{"observed_at":"2026-08-06T15:18:40.293627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:39.960739Z","title":"Cache telepathy: Leverag- ing shared resource attacks to learn {DNN} architectures,","venue":null,"work_id":"be630e11-57f7-4c90-b5e7-feac5c18cf73","year":2020},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.340288Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:21cadc93564ec68e1970fb4ecf87d9af728e49655b7925786975960b6f7718a3","observation_id":"5a0e96b9-4e25-45c7-a9e2-7b04999e8c07","resolution":{"observed_at":"2026-08-06T15:18:40.074993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:39.736261Z","title":"Deeptheft: Stealing dnn model architectures through power side channel,","venue":null,"work_id":"358a0469-d595-49ce-9298-cc37536756f8","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.498105Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:adfeaa939ac7bf7b8b22209de98a63d92a17954a30417f913a337c5ba0942ae2","observation_id":"6ec433e9-ebc2-4a8c-bc16-ca67b4cb669c","resolution":{"observed_at":"2026-08-06T15:18:39.822903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:39.488953Z","title":null,"venue":null,"work_id":"f8a151d3-0e2d-4ea4-90c7-b912d97b2b1f","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.569115Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:4316f8d8db7219576aedc0a15a3d2474ca8491c9c4294d7897a267353b8c2ae9","observation_id":"03b06231-f17a-4151-a7b1-a2b20138b0d7","resolution":{"observed_at":"2026-08-06T15:18:39.602427Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:28.700227Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.700227Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:4866cf825f6d737404b02a241bd7890bd17fc5c485fe93552c79653bd0a74726","observation_id":"cd18d839-7acf-40f7-a9d5-b68a1a4c7e5f","resolution":{"observed_at":"2026-08-06T15:18:28.700227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-07-06T03:53:32.549552Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-06T15:18:28.836237Z","title":"Very deep convolutional networks for large-scale image recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.836237Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:4ca7d9cc594511ce6331f6ce1e128b48797ab6fdaf9234c8a2e5f6165f1f82cc","observation_id":"e31c82a0-6c4d-48b9-823f-9bb48179d9d1","resolution":{"observed_at":"2026-08-06T15:18:28.836237Z","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":"2026-08-06T15:18:39.214558Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks,","venue":null,"work_id":"6c621839-69b8-4b68-bfa4-fb598db39c89","year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:28.943436Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:a72710a5072af39026f09bb8921d4c2991a11010d050044d9116a31f4e8df98b","observation_id":"b6831a87-0bc6-4462-b94e-cde1d2c541e6","resolution":{"observed_at":"2026-08-06T15:18:39.324191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:38.936854Z","title":"Membership inference attacks by exploiting loss trajectory,","venue":null,"work_id":"81ead368-db61-4336-8228-f1654cee35d3","year":2022},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.080570Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:edcd4ab34f4310d3b4f31346dee51af498d21bd08fe7dd6449f24901c5262f2b","observation_id":"fa3ee3e8-7b0a-478c-a128-9220e625993c","resolution":{"observed_at":"2026-08-06T15:18:39.079139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:38.706229Z","title":"Genomic privacy and limits of individual detection in a pool,","venue":null,"work_id":"81b9bef3-a3a2-42a4-b7a1-8494a1fde77a","year":2009},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.220245Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:4e75ffc75a4f4a735dbdec057b68ff0fb6b3d7bce1da9cfdf0c0b412ddcb7fce","observation_id":"84eb7f2c-adeb-4258-a324-c9c1548b8422","resolution":{"observed_at":"2026-08-06T15:18:38.820586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:38.453902Z","title":"A simple weight decay can improve general- ization,","venue":null,"work_id":"54a27f6d-7c24-416e-89fd-fe101df2ae21","year":1991},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.341618Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:24574e617a1eb611a8f374f3c61ffea96884d235bb9c3886d93c38e175c00b9b","observation_id":"b1ed247e-b59f-4d13-b5eb-77d27a00e046","resolution":{"observed_at":"2026-08-06T15:18:38.575903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:29.505975Z","title":"Early stopping-but when?","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.505975Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:222ba5e2bdaebfb6a29cd30f1fe16991a4a6c48221e83c5846196d5699c9bc47","observation_id":"1c9c0b52-70ce-4b22-acc5-5bfff9a9a3d8","resolution":{"observed_at":"2026-08-06T15:18:29.505975Z","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":"2026-08-06T15:18:38.169625Z","title":null,"venue":null,"work_id":"95f0b464-2b85-4944-9b5e-6fdcbd19900b","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.617605Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:485bf705f3a9a1cd6e96810003123c61dda1159535fe81451e58161ed96a9666","observation_id":"1026e189-1879-4bad-ae90-2f68713faf61","resolution":{"observed_at":"2026-08-06T15:18:38.315938Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:37.969701Z","title":"What is the state of neural network pruning?","venue":null,"work_id":"246648ce-42f0-4fca-9fee-6d197df79334","year":2020},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.694255Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:9ca8c89878bbf7365c3677c5d6bd811dfc4370ea92a3ed482bb0619a95106e5b","observation_id":"80b7c21c-3a9a-4e0f-8bce-b1748a5d2d96","resolution":{"observed_at":"2026-08-06T15:18:38.055022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:29.747579Z","title":"On information and sufficiency,","venue":null,"work_id":null,"year":1951},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.747579Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:6479032c3068031aa73361137b486adcc6938f3ae6baba08a1401e4e944cbb7b","observation_id":"2e93cbe6-c523-446d-82e6-018fabeb05d2","resolution":{"observed_at":"2026-08-06T15:18:29.747579Z","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":"2026-08-06T15:18:37.680470Z","title":"Property inference attacks on fully connected neural networks using permu- tation invariant representations,","venue":null,"work_id":"097e1181-d41e-4231-8e9f-e6e73e2317fd","year":2018},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.834749Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:911642243ce8b3cf3ff2be8d0f384f2031bc42e32a8cdad0387367446fdf8cb6","observation_id":"30a8d311-4fed-477e-9426-f60fd65313d0","resolution":{"observed_at":"2026-08-06T15:18:37.828484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:29.895172Z","title":"Deep learning with differential privacy,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:29.895172Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:44524913610fddf54012adbc48b79652d18be53efac615c5813b780b5f48c64c","observation_id":"83f66535-7680-4909-beaf-e7f977cfe5c7","resolution":{"observed_at":"2026-08-06T15:18:29.895172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.03741","last_updated":"2024-09-05T17:54:26Z","snapshot_observed_at":"2026-07-06T19:11:09.921186Z","submitted_at":"2024-09-05T17:54:26Z","title":"Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?","version":1},"cited_work":{"arxiv_id":"2409.03741","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.03741","snapshot_observed_at":"2026-08-06T15:18:33.179852Z","title":"Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?","venue":"cs.CR","work_id":"7d5aead0-b7ce-4aba-a7c7-ff2e9a635fb0","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.023155Z"},"links":{"cited_paper":"/paper/2409.03741","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:cf31440814f8c2ccad3421708f1e141b8a2a77e89423274769b2eb4bebffd2c7","observation_id":"507a3e6d-19e8-42d6-8c85-69cbb9a05af4","resolution":{"observed_at":"2026-08-06T15:18:33.358522Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.08619","last_updated":"2020-03-29T06:05:56Z","snapshot_observed_at":"2026-08-07T09:22:05.626598Z","submitted_at":"2019-08-22T23:09:27Z","title":"Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.08619","snapshot_observed_at":"2026-08-06T15:18:30.141599Z","title":"Efficient task-specific data valuation for nearest neighbor algorithms,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.141599Z"},"links":{"cited_paper":"/paper/1908.08619","citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:546385985624b0fa9adf4a282f0ecc27e95e867767b45989e15b4395426372e4","observation_id":"51bfaa8f-36ae-45ed-84b5-ad3f1edc2868","resolution":{"observed_at":"2026-08-06T15:18:30.141599Z","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":"2026-08-06T15:18:37.546942Z","title":"A comprehensive survey on pretrained foundation models: A history from bert to chatgpt,","venue":null,"work_id":"10fb5158-0009-4042-9ab0-49ebff1a0610","year":2024},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.312735Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:2013b223de6b6d6f16ad4489da089bf701164c885ce292013a9eb0e3664caf47","observation_id":"b9332e60-80a0-4b28-8408-90918b5eae67","resolution":{"observed_at":"2026-08-06T15:18:37.566722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:30.534158Z","title":"Recursive deep models for semantic compositionality over a sentiment treebank,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.534158Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3cc3c5d33f9aa0b5b9f9fbd843f986163ad13c04dd4c49a38a6fd43989878d49","observation_id":"d0f7c49e-0f73-4507-9af1-5d67aedf275d","resolution":{"observed_at":"2026-08-06T15:18:30.534158Z","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":"2026-08-06T15:18:30.687182Z","title":"Calibrating noise to sensitivity in private data analysis,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.687182Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:ff6cd6df594ec5d0ce5834e4adf20365739083f2be20991f919699483fbeac8f","observation_id":"da13f572-9a96-468d-98f6-5f62fb560143","resolution":{"observed_at":"2026-08-06T15:18:30.687182Z","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":"2026-08-06T15:18:30.833104Z","title":"Visualizing data using t-sne","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:30.833104Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:24edbb81fcb5a02a7a78d88a98b9c56bc14703fccafa4496cc2eb76d2d673014","observation_id":"d7c299c8-0b56-4837-a952-6d1709d1583d","resolution":{"observed_at":"2026-08-06T15:18:30.833104Z","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":"2026-08-06T15:18:37.307450Z","title":"Matching networks for one shot learning,","venue":null,"work_id":"d62d6b6d-9f81-4f54-96f8-3e734fe1d2bb","year":2016},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.040658Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:bdb75afdb348c466dffe4aed510204b4f8e10c7d5109ad7605bc183e6f6421af","observation_id":"44ec5842-e8fa-4496-a9f8-66ac1e52d259","resolution":{"observed_at":"2026-08-06T15:18:37.423702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:37.127642Z","title":"Tiny imagenet visual recognition challenge,","venue":null,"work_id":"462aadff-207c-49ea-a07b-24cd5d79f36e","year":2015},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.185966Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:cd496b6de89daffb3834cfdf298741e8c07788587096b8597a00fdc8331f7776","observation_id":"779517dc-5003-4d2e-99bb-36d453a8f979","resolution":{"observed_at":"2026-08-06T15:18:37.200300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:36.869231Z","title":"CIFAR-10","venue":null,"work_id":"6344b38e-79f8-4b30-bbce-ab43224ebb55","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.356334Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:c4aa169db0f46ad3a2d5d7bb25473d7224d6852b4b52ec4d0f5c7402ec2bcbf6","observation_id":"2753c40d-9e81-4717-be67-71742c4ea27f","resolution":{"observed_at":"2026-08-06T15:18:37.053086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:36.565895Z","title":"One method is based on direct concate- nation, i.e., P s o ∥ Ps c ∥ y, and the other is based on calculat- ing the L2 distance, i.e., ∥P s o − Ps c ∥2 ∥ y","venue":null,"work_id":"6995c14d-b450-4a88-aa05-565c3dd31ef5","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.543591Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:975d393e4321be1cfe34d0100169b0d435bd03255f340c36350ddb696965fd19","observation_id":"ede56c0e-a762-4e52-89ed-2645776fc839","resolution":{"observed_at":"2026-08-06T15:18:36.716958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:36.122578Z","title":"TABLE 13: Architecture of the FCN","venue":null,"work_id":"965e7c64-bbb8-40b7-9038-2ff9f4d8ac83","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.729955Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:968a297d44600d84f1316425f042d97a64839f5b7ad9477774a3a7465d16cf70","observation_id":"120c2431-d122-43c1-a2cf-fc4f01cf5403","resolution":{"observed_at":"2026-08-06T15:18:36.331695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:35.740547Z","title":"Evaluation of Pruning","venue":null,"work_id":"9b1320e8-cc6e-4813-942a-8cfa6c56d44d","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:31.853700Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:c5aed7f16bb2884ee8d628be325023d9ad9111ea84fc23b459d7d69bd53db497","observation_id":"abe43e31-dce1-45fe-8cea-1361833870b2","resolution":{"observed_at":"2026-08-06T15:18:35.882968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:35.413529Z","title":null,"venue":null,"work_id":"76ab5b2e-dccf-46ff-9338-05a65f5f4ec3","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.029696Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:aa0b7ddcda16db90d790d854f88634e4c9661e9265264f7de94029a410c91f81","observation_id":"32a47bcf-74ac-415e-946a-11eb9d08f159","resolution":{"observed_at":"2026-08-06T15:18:35.547147Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:35.112793Z","title":null,"venue":null,"work_id":"0b6d988d-d55d-43e3-ab6d-53d30abb6c8c","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.229869Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:6f3cecdb5154f6ca42a2cdd374dea941cfca8f0962bf9fa8f66304f47d4b7ec4","observation_id":"ad941b9c-fe0b-4926-8609-6f293ade062d","resolution":{"observed_at":"2026-08-06T15:18:35.266284Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:34.721262Z","title":"Here, we focus on ex- amining the influence of datasets on attacks by using the same model architecture with different datasets","venue":null,"work_id":"2bd6169c-1928-4891-9a1f-4b8a50dc6f87","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.378581Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:695121aa3fa12280434691c34fc91393a72343efad105b3491f815d1397bb7e7","observation_id":"d038b1bb-4bf1-4266-a5bb-e6eb18bcf234","resolution":{"observed_at":"2026-08-06T15:18:34.876471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:34.374050Z","title":null,"venue":null,"work_id":"6c59a4ef-929e-45d2-b455-ff8cb56dd3f7","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.580686Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:2aae91fb83cc7d0cfb7a28c4f49fa5975b7b376e82d8e385ce6d63a59edb8404","observation_id":"a565354a-300e-421e-b040-af56e230bf99","resolution":{"observed_at":"2026-08-06T15:18:34.527042Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:33.995749Z","title":"To validate the contribution of each meta-data component, we evaluate at- tack performance using each component individually","venue":null,"work_id":"f1522275-4f7b-4480-97c6-d1edd42bc357","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.793828Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:13157f0a0f14ccf100aaa9b0e69f06d06464773d82a183f85edde183df83e140","observation_id":"1821ca56-6079-4b52-9f6b-a72e605a6e66","resolution":{"observed_at":"2026-08-06T15:18:34.199188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:33.626656Z","title":null,"venue":null,"work_id":"c4bcc9b8-3eb1-4aeb-8beb-ca93abdadd1f","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:32.938601Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:601a2c4ca16cdd4488b10c9e19e0e673727171ea90c161f62f5b24287efde00d","observation_id":"30a868b8-079e-426f-9f60-0a37d523dae0","resolution":{"observed_at":"2026-08-06T15:18:33.755583Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T15:18:43.375232Z","title":"Available: https://api.semanticscholar.org/CorpusID: 14089312","venue":null,"work_id":"c2bf8ef1-f2db-4564-b38d-8604038c7fab","year":null},"citing_paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-06T15:18:26.358813Z"},"links":{"citing_paper":"/paper/2507.16872"},"observation_digest":"sha256:3eb486493903abbc74e91072eca36ecc9c0b55038f7ca0443a4af4de939f9612","observation_id":"ffae8ed6-1440-4c34-855c-5bfa8d15e15b","resolution":{"observed_at":"2026-08-06T15:18:43.478058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.16872","last_updated":"2025-07-22T08:02:46Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-06T15:10:12.081789Z","submitted_at":"2025-07-22T08:02:46Z","title":"CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage"},"reference_resolution":{"displayed":89,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":34,"verified_exact":1,"verified_fuzzy":52},"total_outbound_references":89},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 1 inbound Pith citation observation for arXiv:2507.16872."}