{"as_of":"2026-08-09T01:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8c96f43a537aa7447cd4d4dcd73b8f8befe6828ef470e564401ddae659e2918b","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":17,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:41:07.648596Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T07:09:38.117469Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2310.12508","last_updated":"2024-04-04T07:45:38Z","snapshot_observed_at":"2026-08-03T17:30:25.153454Z","submitted_at":"2023-10-19T06:17:17Z","title":"SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation","version":5},"reference_index":117,"source":"arxiv_source","source_observed_at":"2026-05-16T17:56:23.281678Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2310.12508"},"observation_digest":"sha256:d4e11be77ed7e1d8d87713eb637d9ee90863cf169980ae0276a507a531d50e1f","observation_id":"6c354658-3a57-4c0a-abb3-defdd49047f8","resolution":{"observed_at":"2026-05-16T17:56:23.495209Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2405.00892","last_updated":"2026-04-30T18:09:59Z","snapshot_observed_at":"2026-07-06T18:08:30.875909Z","submitted_at":"2024-05-01T22:33:45Z","title":"Wake Vision: A Tailored Dataset and Benchmark Suite for TinyML Computer Vision Applications","version":6},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-24T01:06:48.298874Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2405.00892"},"observation_digest":"sha256:95f9f058133dd7dd8f865bc8a457db8ce7d2b257a19540ab1f97fba9c446e38a","observation_id":"9c28810d-e176-448f-866a-0f031a981a10","resolution":{"observed_at":"2026-05-24T01:08:41.918296Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-07T14:41:07.648596Z","title":"What do compressed deep neural networks forget? arXiv preprint arXiv:1911.05248, 2019","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2505.18015","last_updated":"2025-05-23T15:17:45Z","snapshot_observed_at":"2026-08-07T23:41:34.613590Z","submitted_at":"2025-05-23T15:17:45Z","title":"SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:41:07.648596Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2505.18015"},"observation_digest":"sha256:d880710957889014c5100d2876e9eeb2a92cefa2fc02f632048bf79a3d996b9d","observation_id":"b3572c33-a571-4546-aa11-107e1c90fd6d","resolution":{"observed_at":"2026-08-07T14:41:07.648596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-06T15:32:01.096012Z","title":"What do compressed deep neural networks forget?","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2507.15636","last_updated":"2025-07-21T13:58:24Z","snapshot_observed_at":"2026-08-07T18:19:49.953174Z","submitted_at":"2025-07-21T13:58:24Z","title":"Uncovering Critical Features for Deepfake Detection through the Lottery Ticket Hypothesis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:01.096012Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2507.15636"},"observation_digest":"sha256:c799fd2a83bca8d2270385655f906a2b92beb3a38cfc0fa1b9155e55e0cae0b2","observation_id":"771deed6-1eea-4371-abac-05632ab067b9","resolution":{"observed_at":"2026-08-06T15:32:01.096012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-05T22:09:04.257495Z","title":"What do compressed deep neural networks forget? arXiv preprint arXiv:1911.05248, 2019","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2508.07556","last_updated":"2025-09-06T12:35:53Z","snapshot_observed_at":"2026-08-07T08:21:13.704669Z","submitted_at":"2025-08-11T02:33:53Z","title":"Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning","version":2},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-05T22:09:04.257495Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2508.07556"},"observation_digest":"sha256:10f9397f5a546218990d3d31eb19ddf23c22a07412cf171ee4f0b09aa0c1998a","observation_id":"7d9d0386-5dd7-48a9-a5b8-9cd7ba88c11f","resolution":{"observed_at":"2026-08-05T22:09:04.257495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-05T19:00:30.057802Z","title":"https://arxiv.org/abs/1911.05248","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2508.13533","last_updated":"2025-08-19T05:49:39Z","snapshot_observed_at":"2026-08-07T10:33:49.568008Z","submitted_at":"2025-08-19T05:49:39Z","title":"Compressed Models are NOT Trust-equivalent to Their Large Counterparts","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-05T19:00:30.057802Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2508.13533"},"observation_digest":"sha256:c354ae7a46ac298e9fb70c91d523bdf9c6e6adac0969c6005d9d05ea62f8be73","observation_id":"abfd3e7b-a141-4625-b034-9abe1f94a506","resolution":{"observed_at":"2026-08-05T19:00:30.057802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-05T14:49:26.502581Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.20893","last_updated":"2025-08-28T15:22:31Z","snapshot_observed_at":"2026-08-05T14:49:11.492918Z","submitted_at":"2025-08-28T15:22:31Z","title":"The Uneven Impact of Post-Training Quantization in Machine Translation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-05T14:49:26.502581Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2508.20893"},"observation_digest":"sha256:2823a5b67ac7656d41b5a5849ebc65b05b41f74fe3be1aa9829e30a73c4e385e","observation_id":"276e11e4-bdf9-451d-a32e-1208416452e2","resolution":{"observed_at":"2026-08-05T14:49:26.502581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-04T22:41:17.308780Z","title":"What do com- pressed deep neural networks forget?arXiv preprint arXiv:1911.05248,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2509.07222","last_updated":"2025-09-08T21:04:16Z","snapshot_observed_at":"2026-08-08T03:54:15.832631Z","submitted_at":"2025-09-08T21:04:16Z","title":"Explaining How Quantization Disparately Skews a Model","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-04T22:41:17.308780Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2509.07222"},"observation_digest":"sha256:535f0a1adb913c7f8679d54f9d9586cd40cc1e13d33ed84477c09f48578b1d51","observation_id":"96659789-0933-43bf-b38f-47269ae135d2","resolution":{"observed_at":"2026-08-04T22:41:17.308780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2603.05582","last_updated":"2026-05-12T21:44:20Z","snapshot_observed_at":"2026-08-07T22:52:22.533634Z","submitted_at":"2026-03-05T18:54:24Z","title":"Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-15T16:14:35.756456Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2603.05582"},"observation_digest":"sha256:573b9c105ef3f3ebff989dca5c152c97971296ca339e68c7b106226899fe35a6","observation_id":"5de1d058-fa26-4ca9-bf49-daef29b63585","resolution":{"observed_at":"2026-05-15T16:16:15.094198Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2605.01597","last_updated":"2026-05-02T20:11:12Z","snapshot_observed_at":"2026-08-03T00:52:48.762187Z","submitted_at":"2026-05-02T20:11:12Z","title":"Toward Fair Speech Technologies: A Comprehensive Survey of Bias and Fairness in Speech AI","version":1},"reference_index":272,"source":"pdf_text","source_observed_at":"2026-05-08T19:27:18.774649Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2605.01597"},"observation_digest":"sha256:a4fd3c98c6db0e627865de8b2412fa7a9956e4fe7eaa466ca9700e641eacb8e4","observation_id":"e6731ec8-7aa3-45a3-a1cc-d275ef3e5fb3","resolution":{"observed_at":"2026-05-09T05:50:28.356500Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2605.08137","last_updated":"2026-05-02T05:27:40Z","snapshot_observed_at":"2026-07-26T17:20:12.102392Z","submitted_at":"2026-05-02T05:27:40Z","title":"Weight Pruning Amplifies Bias: A Multi-Method Study of Compressed LLMs for Edge AI","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-12T02:50:17.302744Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2605.08137"},"observation_digest":"sha256:00ae9098f62e34a367f9c52eca714c5b5bff0805e3dffb3d0ebdc1fab93443c7","observation_id":"36f2077d-1083-4a6e-ae24-ae8f012aad28","resolution":{"observed_at":"2026-05-12T02:51:17.635904Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2605.15208","last_updated":"2026-05-02T05:41:47Z","snapshot_observed_at":"2026-08-08T23:09:32.922093Z","submitted_at":"2026-05-02T05:41:47Z","title":"Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-19T17:55:35.764347Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2605.15208"},"observation_digest":"sha256:3d60401726c7395910dbb01b558b49541d0173686f7a9bd2e97d6e278bb28189","observation_id":"98905bc3-8204-4352-937a-2a3a3036ddc9","resolution":{"observed_at":"2026-05-19T17:57:42.535481Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2606.09924","last_updated":"2026-06-07T09:19:44Z","snapshot_observed_at":"2026-08-06T21:59:37.548010Z","submitted_at":"2026-06-07T09:19:44Z","title":"Sigma-Branch: Hierarchical Single-Path Network Reconstruction for Dynamic Inference with Reduced Active Parameters","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T18:41:57.062611Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2606.09924"},"observation_digest":"sha256:bf3ffef3bac4ac26073e3e6ef5326d51dac1e20dfc87445749f0cd17a883c88c","observation_id":"f7ef2040-aca6-4d23-b088-915aa3f43b39","resolution":{"observed_at":"2026-07-02T22:37:26.594718Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2606.12234","last_updated":"2026-06-10T15:42:15Z","snapshot_observed_at":"2026-08-05T00:08:40.346158Z","submitted_at":"2026-06-10T15:42:15Z","title":"On The Effectiveness-Fluency Trade-Off In LLM Conditioning: A Systematic Study","version":1},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-06-27T09:40:48.736006Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2606.12234"},"observation_digest":"sha256:3f6b8d31ae0ba99c5db33f8dc2f9b43c98f678f5ea6abe9fe57bf4cc8428059c","observation_id":"125b98df-95f0-4277-ac2f-33c276d842b5","resolution":{"observed_at":"2026-07-03T11:08:03.524534Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2606.21101","last_updated":"2026-06-19T05:05:40Z","snapshot_observed_at":"2026-08-06T12:01:02.956634Z","submitted_at":"2026-06-19T05:05:40Z","title":"DPIFrame: A Dual-Level Parallelism Acceleration Framework for CTR Model Inference","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-26T13:42:59.458894Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2606.21101"},"observation_digest":"sha256:d5c1f9212aff3d007488065ad279cb898b213c42a2cfd59ac4ac8975b31b1cef","observation_id":"6836beab-1e7e-4fce-803b-62c216bcecd1","resolution":{"observed_at":"2026-07-04T07:09:38.118891Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":"1911.05248","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-07-04T07:09:38.117469Z","title":"What do compressed deep neural networks forget?arXiv preprint arXiv:1911.05248","venue":null,"work_id":"c9bc3423-e8b9-4934-b941-fe282832d49d","year":1911},"citing_paper":{"arxiv_id":"2607.02237","last_updated":"2026-07-02T14:34:31Z","snapshot_observed_at":"2026-07-07T00:07:42.752664Z","submitted_at":"2026-07-02T14:34:31Z","title":"When Token Compression Breaks: Structural Pruning vs. Token Reduction for Robust ViT Segmentation under High Compression","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-03T15:51:31.726148Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2607.02237"},"observation_digest":"sha256:4437351336d0dcf30fe37e0d9d6f5d3275b8cf726ef2c94bd97d7bca55791387","observation_id":"0bdf643e-8dcb-4836-9a6a-5ff7d93902fb","resolution":{"observed_at":"2026-07-03T15:58:37.550540Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.05248","snapshot_observed_at":"2026-08-01T08:38:54.456189Z","title":"2019 , note=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.21063","last_updated":"2026-07-23T08:56:11Z","snapshot_observed_at":"2026-08-07T01:50:19.863208Z","submitted_at":"2026-07-23T08:56:11Z","title":"QuantiBias: Benchmarking Quantization-Induced Bias in LLMs","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-01T08:38:54.456189Z"},"links":{"cited_paper":"/paper/1911.05248","citing_paper":"/paper/2607.21063"},"observation_digest":"sha256:91fb0536d8051054757df9cabc44d07404dd30d0fa2850c2c6acd2b9c83ae0df","observation_id":"7e2a7743-27ca-4730-8b53-e73a8f7daf1c","resolution":{"observed_at":"2026-08-01T08:38:54.456189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1911.05248/citation-record","integrity":"/paper/1911.05248/integrity","json":"/paper/1911.05248/citation-record.json","paper":"/paper/1911.05248"},"outbound":[],"paper":{"arxiv_id":"1911.05248","last_updated":"2021-09-06T00:47:17Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T08:36:35.767733Z","submitted_at":"2019-11-13T02:02:19Z","title":"What Do Compressed Deep Neural Networks Forget?"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:1911.05248."}