{"as_of":"2026-08-16T07:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e4d44565d377a3a533cb1e87ddc7bbd794fe06159b2a3852e24efb63106015ac","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:02:42.430727Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.03995/citation-record","integrity":"/paper/1908.03995/integrity","json":"/paper/1908.03995/citation-record.json","paper":"/paper/1908.03995"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:02:43.696694Z","title":"Security and privacy cha llenges in the smart grid,","venue":null,"work_id":"6559df4e-02eb-42d2-9f37-231ac921a0df","year":2009},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.046228Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:1a32ec8e7c33a8ad50c9a585ce9ef75e149be296cf1fc52c02eeeff728abd25e","observation_id":"81524e4e-fab9-424f-a46a-9630bdbcf0aa","resolution":{"observed_at":"2026-08-14T14:02:43.705544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.662947Z","title":"Multimedia conten t identification through smart meter power usage profiles,","venue":null,"work_id":"6aa03a4a-3151-4efd-a2e0-a4ee0ed3e64a","year":2012},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.065370Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:1170cc92d6ce21d559b935e37c418a732560c94436410a294dff66db3d9bf898","observation_id":"70c883cc-a2b2-460a-a7de-8e753ac6bc09","resolution":{"observed_at":"2026-08-14T14:02:43.669645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.638610Z","title":"Non- intrusive load monitoring through home energy management s ystems: A comprehensive review,","venue":null,"work_id":"f6fe3b39-650d-4742-a72b-35e9086672ad","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.078956Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:133ec6f6f7fce4fb7c0ad9b8d891e8f678bef61072b1956379eff836185bd9f2","observation_id":"6f6768d6-fd04-41d3-aee1-ef829730eafa","resolution":{"observed_at":"2026-08-14T14:02:43.645526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.619406Z","title":"Smart metering and privacy in Europe: lessons from the Dutch case,","venue":null,"work_id":"4dab9f09-f511-4c97-a166-8f8bba6ce239","year":2013},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.087230Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:3ee200c7bcc3c84c1dcebd6124722d9da22a52f08bda0f5a270aef82b0e6e00f","observation_id":"de86eae3-31ea-4dea-bc10-a2ca1b97d7a8","resolution":{"observed_at":"2026-08-14T14:02:43.626005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.594767Z","title":"The algorithmic foundations of dif ferential privacy,","venue":null,"work_id":"4c87c268-4678-4485-b70d-5b89f965363e","year":2014},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.101352Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:4a140bcb8c660167a7815c8b83a147fe5e3987f67836ee54c1638432d86d3235","observation_id":"c88108f4-da79-4d13-a0dc-52394570bee9","resolution":{"observed_at":"2026-08-14T14:02:43.605975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.564228Z","title":"Calibrat ing noise to sensitivity in private data analysis,","venue":null,"work_id":"85b48a86-4c47-4239-9731-865cfbaaf736","year":2006},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.117419Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:db10d7a2de3b5910a1ac60d10c5c62b040a1a5ec41c59fe9c095f40f2a50dc0c","observation_id":"1a4c5e0a-5abf-4332-a9c9-4ac256677ae6","resolution":{"observed_at":"2026-08-14T14:02:43.570629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.538102Z","title":"Differential privacy,","venue":null,"work_id":"0d2f6756-a168-4688-b4e6-f244a4b8ea46","year":2006},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.124393Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:001c0d66103320f2b91ac7534ae69e8c41741d304240ab61d7e496f308270a8a","observation_id":"f8545bb0-c086-4e03-8139-2fd82e3fee99","resolution":{"observed_at":"2026-08-14T14:02:43.549293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.516541Z","title":"Local dif ferential pri- vacy for evolving data,","venue":null,"work_id":"f025850e-157f-41fd-8601-45cef9849bbd","year":2018},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.130846Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:702ddcf58ea59fb6c2c0c9e0b18a60136f981605b570e6ce57162c66df52ee52","observation_id":"a5031bed-ec02-40e4-9590-18ef0756e77d","resolution":{"observed_at":"2026-08-14T14:02:43.523521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.492830Z","title":"Differ ential privacy under continual observation,","venue":null,"work_id":"76c3bd11-87a6-457f-b291-f673ecddcd4b","year":2010},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.143791Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:343fb02e0f20c672d8deddc514c434a3ce1c6e5f7853ac72c171ca55abb40a06","observation_id":"bddf0e48-c6b3-48ce-8283-4417244b03c8","resolution":{"observed_at":"2026-08-14T14:02:43.502571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.464344Z","title":"Private and continua l release of statistics,","venue":null,"work_id":"2e5d61b4-54ba-4dbc-b04d-038d47692511","year":2011},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.150974Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:fc306e0018a02506b7ec7462506cd05ad2212d6c59a548e20b313e346d4eaab5","observation_id":"b127f5e1-ba08-459f-b03a-4b32f6507c77","resolution":{"observed_at":"2026-08-14T14:02:43.472978Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.438458Z","title":"Private contin ual release of real-valued data streams,","venue":null,"work_id":"5d2d4740-2a83-47b6-96c7-bff5050b22cb","year":2019},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.158551Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:ddb3525549e22dc7cf6dad3c74df0629fcfda48cfa903783549adbb9ade61fcd","observation_id":"4eecbd72-aeb5-4d03-aea7-a696af8f075d","resolution":{"observed_at":"2026-08-14T14:02:43.447648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.410996Z","title":"Differen- tial privacy for growing databases,","venue":null,"work_id":"ee78fd9f-6099-468c-981e-412905a41c28","year":2018},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.166980Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:4c626d97866fb2a003b8bec2bc8d97e44791abfec471d3a3cd47a032d30e0257","observation_id":"c932d8c9-fa67-492d-8bcc-abd9b904ec21","resolution":{"observed_at":"2026-08-14T14:02:43.421560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.385976Z","title":"The complexity of differential privacy,","venue":null,"work_id":"2c825078-c90a-40c5-a3c8-cc6705e8de69","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.178712Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:7c9bf047193686cf21e6af64c13819699b8c59107cf0bdc1ac17d3e0699de7db","observation_id":"c71aada7-a81c-4151-83be-c77e7eee1942","resolution":{"observed_at":"2026-08-14T14:02:43.392941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.357125Z","title":"Differentially private kalma n filtering,","venue":null,"work_id":"134c3623-2914-4b7f-be74-e139e5be1d96","year":2012},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.186819Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:883f4dfbeed0fa78bec762129208966060c76c0480c0bf3c732d0bafac0b811f","observation_id":"fa1646a4-7227-4a32-aa35-bbb65d33d9d1","resolution":{"observed_at":"2026-08-14T14:02:43.364323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.332702Z","title":"Differentially private filter ing,","venue":null,"work_id":"12282c5a-56b1-415a-aa5f-72f33a9702b0","year":2013},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.196152Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:ce627c72476166a93019fab51a6a82993f5239ca0661331ecfe045fe741f30e0","observation_id":"416dbd65-8577-4335-9dc2-57dfcfe0bfeb","resolution":{"observed_at":"2026-08-14T14:02:43.341578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.309094Z","title":"Differential privacy in control and network systems,","venue":null,"work_id":"ce283bb4-cc80-48c0-90f6-3dc8e335b4a6","year":2016},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.203958Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:25ba4d10c9f3c8895a84e41987047670161974e8dfb6776dd77cfd6e8c9937b5","observation_id":"b4e196e1-408d-4417-a421-de1bfa230a1d","resolution":{"observed_at":"2026-08-14T14:02:43.317429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.271605Z","title":"Differe ntial privacy in linear distributed control systems: Entropy minimizing mechanisms and performance tradeoffs,","venue":null,"work_id":"625b2291-da74-4524-8219-32609fa49cb1","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.214463Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:a6c94663bd66b38654acbbe6319b18e96b237a70ebe5f16540cab906fc3a5ffc","observation_id":"f8eb4cd3-440f-4fd1-b909-005bf2f4cbfe","resolution":{"observed_at":"2026-08-14T14:02:43.288184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.249101Z","title":"Privacy in control and dynamica l systems,","venue":null,"work_id":"362b7e08-ddef-4258-be4e-0a004cfbd904","year":2018},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.220494Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:6c0bb849af8b22ec0afdce7cb847fbdce029067413879ff44d94f1c43b23d90c","observation_id":"4ef079db-8c60-4dff-ab55-a2bd0ddf17b8","resolution":{"observed_at":"2026-08-14T14:02:43.255291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.218838Z","title":"Differentially private MIMO filtering for event streams,","venue":null,"work_id":"6fa19d46-e0e2-42fa-ad91-301d43586a67","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.226570Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:d39ed6f1ce1229863e5591c75cd0744269994d27cf9b66950528a62dcd5132f6","observation_id":"aa30cd8d-4450-4ed2-86ba-94289bc3cadf","resolution":{"observed_at":"2026-08-14T14:02:43.228415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.169426Z","title":"Differentially priv ate distributed constrained optimization,","venue":null,"work_id":"da071d44-1fbe-4baf-8038-bb745c6dd51b","year":2016},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.233154Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:59b396f0ee1ffc3f6fa6b93b95250d46a791311f847e39c11c13dad257969c20","observation_id":"de975971-46e2-4d64-9aac-542fcb3b9745","resolution":{"observed_at":"2026-08-14T14:02:43.195465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.140394Z","title":"Different ially private average consensus with optimal noise selection,","venue":null,"work_id":"d1b92163-8c11-4abf-a51c-b5c3f4a82ffd","year":2015},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.238916Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:d0423df172c48ab73cdb06e6a9c77eb063d616be6e16e2d209d4fa4fae486a63","observation_id":"6a79b255-ba51-41c5-9845-457ae184fefa","resolution":{"observed_at":"2026-08-14T14:02:43.146282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.112939Z","title":"Privacy preserving average cons ensus,","venue":null,"work_id":"590a7d2b-8326-4e14-bae6-a920b8d90312","year":2016},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.245010Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:dffb7902b57b5dfbb85f2e38605d5b517a66a1ba60906c10f5bed2f6112ae460","observation_id":"57fde32f-f3a8-4e48-b728-a6af6e582005","resolution":{"observed_at":"2026-08-14T14:02:43.118281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.089864Z","title":"Different ially private average consensus: Obstructions, trade-offs, and optimal algorit hm design,","venue":null,"work_id":"a574d52e-539a-43a5-a1d8-5597bea676ff","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.251279Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:3324c409aa6aa5485fde4b6b1bbe2ec5a767b2b5a1eaf73ca320576094656e0c","observation_id":"e0e8a5b6-28c0-4566-a655-164ef09c1474","resolution":{"observed_at":"2026-08-14T14:02:43.097629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.055423Z","title":"Discounting of delayed reward s: Models of individual choice,","venue":null,"work_id":"6a122c0e-df32-455e-a5a5-e815c884cd4d","year":1995},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.259593Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:c8bd7ff675aed303699906e20f512cd4eb498cba4a20317873fb838d60bcced4","observation_id":"ca2d6416-ef8d-43d7-a3a9-03527186c8a1","resolution":{"observed_at":"2026-08-14T14:02:43.063444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:43.029354Z","title":"Intertemp oral choice– toward an integrative framework,","venue":null,"work_id":"74ada756-4221-4881-a190-842421ace5d1","year":2007},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.274846Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:fc3fbc3848ed3a5e2238bf46fed0e259612661bf90cf85a0dedc04fc79b4b991","observation_id":"49ce4565-3b32-4d7c-bca1-bcc96bda75e7","resolution":{"observed_at":"2026-08-14T14:02:43.038469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.990302Z","title":"A mathematical theory of saving,","venue":null,"work_id":"714fe1aa-f893-445a-9573-d7ffce1e3699","year":1928},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.282243Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:fb5fcafd1ec0c032905cd7132a0317abc1c5e361ca1bc718146f580fbbae5185","observation_id":"461ff36d-d6f4-4bb8-b3e8-5aeaebe08757","resolution":{"observed_at":"2026-08-14T14:02:43.002080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.957588Z","title":"A note on measurement of utility,","venue":null,"work_id":"171a133e-4200-467c-92b6-682c4a16e549","year":1937},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.291805Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:e265c2321c017ffe9b5d38ccf0a7f9a64a43ca68815f5a70b667bf17e3f79118","observation_id":"fc304371-f0b1-4629-b8c8-cccdb5dc185a","resolution":{"observed_at":"2026-08-14T14:02:42.965069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.931300Z","title":"Specious reward: A behavioral theory of im pulsiveness and impulse control,","venue":null,"work_id":"c09ed705-99d3-4178-bd10-d2420465d766","year":1975},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.299849Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:511163e05363e6c012901bd51a95f1fab175803d1d27568be73f9075fcdddb17","observation_id":"c5f86168-e7da-4417-bfe6-04727ead74d7","resolution":{"observed_at":"2026-08-14T14:02:42.939409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.904505Z","title":"Impulse control in pigeons,","venue":null,"work_id":"ce1bc952-be82-4b9e-81b3-148fdf197959","year":1974},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.311267Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:486be75bf7c9534785137049e451eb83a1a20d5ce45ac2de570b430d5f898c2b","observation_id":"a73c7967-151d-4ab6-8f29-032ffb85f898","resolution":{"observed_at":"2026-08-14T14:02:42.911891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.876038Z","title":"Preference reversal a nd delayed reinforcement,","venue":null,"work_id":"93cdf325-16b9-4a4d-aa41-4e826c83fc56","year":1981},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.320500Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:4e8610cce7a50c5b9d8df4c89076f5f503b8b999af298a7c9f108fd402f5dabd","observation_id":"3602f418-2a68-46df-b0de-5a4b66e243e8","resolution":{"observed_at":"2026-08-14T14:02:42.882951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.853835Z","title":"Bidding on the future: Evidence against no rmative discounting of delayed rewards,","venue":null,"work_id":"aadc4907-d83d-46ab-aeed-aeafbb0b4eb5","year":1997},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.328903Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:bfc02d0f4d9bea417900e524da119b4d849fcce3c8c09daf94b47754422f7f60","observation_id":"d13286f0-f5bb-4da8-a474-e8fac916ccbb","resolution":{"observed_at":"2026-08-14T14:02:42.859761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.808459Z","title":"Hyperbolic temporal discounting in social drinkers and problem drinkers,","venue":null,"work_id":"b0789b06-5aa0-4c06-ae7d-7fd5dff8048b","year":1998},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.335341Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:c71fe2f97d4238b0674993b2c641983c1e10ce91700a52e5dd031cbada12ddb4","observation_id":"6a7ad761-9fe8-4269-93aa-171d762df471","resolution":{"observed_at":"2026-08-14T14:02:42.820408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.780145Z","title":"Privacy and self-discl osure in social relationships,","venue":null,"work_id":"c16e9ce1-a7fb-49a2-aaf0-a32b343a05bb","year":1977},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.345441Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:ff62d3ffbb3ba4e1a5ea4d72372d467937ae06956daf887a5762db26b4c95230","observation_id":"23f00785-0daf-47ad-ab9f-99da131c2619","resolution":{"observed_at":"2026-08-14T14:02:42.787547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.754256Z","title":"Australian so cial trends December 2010: Moving house,","venue":null,"work_id":"4259614d-4b83-4865-83c8-d48a1a0b0299","year":2010},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.353346Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:e764cd5981134316dd22f28100c2284b750a11cbff5cd9ff99fac1751eae7e16","observation_id":"83458716-11bc-43c3-8648-f8ba6583bfdb","resolution":{"observed_at":"2026-08-14T14:02:42.766227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.720687Z","title":"Privacy attitudes and p rivacy behavior,","venue":null,"work_id":"1bf28b40-5d52-4165-9817-308c478a2fca","year":2004},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.360617Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:da3419575450d6b8c308495391bfc6889bff2e24d9e484733ff262400054d0cf","observation_id":"2b85f1d2-3db9-4550-93ee-a348e08902b0","resolution":{"observed_at":"2026-08-14T14:02:42.732904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.675842Z","title":"The right to be forgotten,","venue":null,"work_id":"a6c55243-4dc5-4591-80f4-11a185c57eb2","year":2011},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.369199Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:e6a499246267b6083e97057c1067e51afa95591fb86f6bf59d382cd2d0d565d8","observation_id":"358b3d51-ec22-4a04-bc96-af21c29dcbec","resolution":{"observed_at":"2026-08-14T14:02:42.688815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.648033Z","title":"Personalization versus p rivacy: An empirical examination of the online consumer’s dilemma,","venue":null,"work_id":"ec4eb811-431f-48b4-ae3c-10f35baea503","year":2005},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.377886Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:0d368346f1d8009152e2d74babaa7642907ac01710476dc835181983630611cd","observation_id":"12142506-64c3-4077-9ed7-42313583059c","resolution":{"observed_at":"2026-08-14T14:02:42.656085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.616884Z","title":"E-priv acy in 2nd generation e-commerce: Privacy preferences versus actual behavior,","venue":null,"work_id":"04495ae4-a9ad-4dd6-9615-2c7cf99b1e9f","year":2001},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.387862Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:dfb0a369c0bc7eb5b9374bde578741b17be80de1a51b51f1dbf148d20c97e27d","observation_id":"c576aaa8-5711-486e-94a8-935f27ff8018","resolution":{"observed_at":"2026-08-14T14:02:42.625615Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.584498Z","title":"Private decayed predicate sums on streams,","venue":null,"work_id":"e77f6402-ae29-47f0-bc7e-11e6afbed710","year":2013},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.395337Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:0c991bd0496a4ecf8cbb79817268f23eb4ece0e990be4c43481f02bef3c1d6da","observation_id":"36ae44ec-8b57-4f86-8c9a-f84817b7a403","resolution":{"observed_at":"2026-08-14T14:02:42.590897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.555137Z","title":"Differentially private event sequences over infinite streams,","venue":null,"work_id":"93287703-16b8-4da5-85fb-b1833cc06db7","year":2014},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.406458Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:ea4685f3da145d771b8bb60250ac80c50ebedc296f95d8ca7cd07557fa3295d0","observation_id":"e0ef70c9-7153-4b16-9988-72d35462bcca","resolution":{"observed_at":"2026-08-14T14:02:42.564823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.514532Z","title":"Peg asus: Data- adaptive differentially private stream processing,","venue":null,"work_id":"6b57dab1-8cb9-4d9a-af0f-d253676d8ee9","year":2017},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.419585Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:e0fd46f2f723923511dfb75cfa348f48cc4e58a655e5dda49cadfcb06945e46a","observation_id":"00e27ea8-f226-40a9-b967-9bdd97f90817","resolution":{"observed_at":"2026-08-14T14:02:42.530766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T14:02:42.487988Z","title":"Solar home electricity data,","venue":null,"work_id":"f5b4a1ef-757c-4a3a-8c3e-b1175ae26850","year":2014},"citing_paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T14:02:42.430727Z"},"links":{"citing_paper":"/paper/1908.03995"},"observation_digest":"sha256:463b905c0d5dd07f11f55f8b95d3d2dccc8636a3d4ad6b9610ed6d2296b450e9","observation_id":"7aeffdc6-0aca-4897-9d50-a3e2dd47da12","resolution":{"observed_at":"2026-08-14T14:02:42.496589Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.03995","last_updated":"2020-01-28T00:59:03Z","latest_version":2,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-16T03:26:50.334411Z","submitted_at":"2019-08-12T04:25:54Z","title":"Temporally Discounted Differential Privacy for Evolving Datasets on an Infinite Horizon"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":42},"total_outbound_references":42},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:1908.03995."}