{"as_of":"2026-08-08T07:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2884b1e598ece1a5b43575bf028f39873aea65c4ef5ce226bab3bf754af5a400","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":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":19,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:29:53.662752Z","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":"2026-07-01T15:05:47.561630Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2405.07406","last_updated":"2026-04-20T05:27:15Z","snapshot_observed_at":"2026-07-06T18:13:16.171803Z","submitted_at":"2024-05-13T00:58:34Z","title":"Machine Unlearning: A Comprehensive Survey","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-24T01:13:26.620111Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2405.07406"},"observation_digest":"sha256:e5bd7574a9cb49a79643ca9f524e049952db61005a2dd8db0681536fea45defe","observation_id":"b0bd43ee-9dba-433b-9291-486ff7f1bdda","resolution":{"observed_at":"2026-05-24T01:13:42.716014Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-07T00:29:53.662752Z","title":"and Deja, K","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14014","last_updated":"2025-06-16T21:26:01Z","snapshot_observed_at":"2026-08-07T00:22:28.659973Z","submitted_at":"2025-06-16T21:26:01Z","title":"Beyond Black Boxes: Enhancing Interpretability of Transformers Trained on Neural Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:29:53.662752Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2506.14014"},"observation_digest":"sha256:de3ac086e70a244088bceae930d77d0a8bac705e449156e5882651ecb0592571","observation_id":"da0c16e6-ccc8-416e-81f3-5a11ceef6395","resolution":{"observed_at":"2026-08-07T00:29:53.662752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-06T16:51:52.584625Z","title":"arXiv preprint arXiv:2501.18052 (2025) 10 Dasdelen et al","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.12464","last_updated":"2025-07-16T17:59:32Z","snapshot_observed_at":"2026-08-07T18:12:41.445155Z","submitted_at":"2025-07-16T17:59:32Z","title":"CytoSAE: Interpretable Cell Embeddings for Hematology","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:52.584625Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2507.12464"},"observation_digest":"sha256:fd1f8860c362b1d4dd8626a8f485f9c45ee95bf6e0867ab1d633f5c13c912c75","observation_id":"0948aa01-7971-4734-9463-b8d9d28ee367","resolution":{"observed_at":"2026-08-06T16:51:52.584625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-04T15:42:35.981962Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoen- coders.arXiv preprint arXiv:2501.18052, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.21379","last_updated":"2026-05-29T14:42:07Z","snapshot_observed_at":"2026-08-04T15:42:31.963286Z","submitted_at":"2025-09-23T11:29:30Z","title":"SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T15:42:35.981962Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2509.21379"},"observation_digest":"sha256:d8ce4321aaadf8463c507751a8918e352e7825990d06fb11192022a7cc945bfc","observation_id":"5ebdd2ad-7eb3-47f4-9f95-e09d07b3ecf8","resolution":{"observed_at":"2026-08-04T15:42:35.981962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-03T19:48:42.718198Z","title":"& Deja, K","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2511.22519","last_updated":"2026-06-07T16:22:01Z","snapshot_observed_at":"2026-08-03T19:48:41.463804Z","submitted_at":"2025-11-27T14:54:00Z","title":"FoldSAE: Learning to Steer Protein Folding Through Sparse Representations","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T19:48:42.718198Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2511.22519"},"observation_digest":"sha256:2cdb07788817164e55a178492d0026c9c959152cedf8bc907b2d155fc364cf43","observation_id":"d8fa6bdb-fdee-4892-9078-42cdff5c0080","resolution":{"observed_at":"2026-08-03T19:48:42.718198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-03T18:33:01.760714Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.05038","last_updated":"2026-05-29T17:42:38Z","snapshot_observed_at":"2026-08-07T15:13:01.011752Z","submitted_at":"2025-12-04T17:55:55Z","title":"The SuperActivator Mechanism: Transformers Concentrate Reliable Concept Signals in the Tail","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T18:33:01.760714Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2512.05038"},"observation_digest":"sha256:a638f356d73963bdd93c8e6da47ef3e97b632729934daef85a3b6bd471c6cab1","observation_id":"879c1a66-288b-45e2-a1eb-802a5c7deac4","resolution":{"observed_at":"2026-08-03T18:33:01.760714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-03T05:05:53.541076Z","title":"and Deja, K","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.03410","last_updated":"2026-06-03T20:46:40Z","snapshot_observed_at":"2026-08-03T05:05:52.770581Z","submitted_at":"2026-02-03T11:37:08Z","title":"UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T05:05:53.541076Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2602.03410"},"observation_digest":"sha256:f7e239b61f5178dc895a810c13c6afd4748be7e526918bd2b4ab567a7f493b35","observation_id":"995d4e43-6038-4050-ae1f-9792faae8089","resolution":{"observed_at":"2026-08-03T05:05:53.541076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-02T21:27:18.974138Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.00133","last_updated":"2026-06-01T15:15:09Z","snapshot_observed_at":"2026-08-07T09:44:34.146120Z","submitted_at":"2026-02-23T17:20:40Z","title":"You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T21:27:18.974138Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2603.00133"},"observation_digest":"sha256:a09df58511ceef2388bd9e3b1789848a7a75f02bb42053271af9ea70a8f0d1a7","observation_id":"106922a2-0278-4806-8e2e-c5b4ccc8824c","resolution":{"observed_at":"2026-08-02T21:27:18.974138Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2604.10032","last_updated":"2026-04-11T05:06:15Z","snapshot_observed_at":"2026-07-06T22:58:43.155246Z","submitted_at":"2026-04-11T05:06:15Z","title":"Closed-Form Concept Erasure via Double Projections","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T16:44:57.265729Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2604.10032"},"observation_digest":"sha256:dc1d8b1d524ccb6281ca0209ab1d623b9e4632eccb747a356f531877247c985d","observation_id":"a9b2ce30-3f8f-4eee-a542-b4176bc1e11e","resolution":{"observed_at":"2026-05-11T08:16:00.787364Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2604.14925","last_updated":"2026-04-16T12:10:08Z","snapshot_observed_at":"2026-07-06T23:02:36.062162Z","submitted_at":"2026-04-16T12:10:08Z","title":"Improving Sparse Autoencoder with Dynamic Attention","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T11:07:24.389139Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2604.14925"},"observation_digest":"sha256:83fd69439235965ef7d490d169f14d1323db1291aa763821059f4e9b9ff3ae0d","observation_id":"6575709d-2156-4424-b6df-5472862c4bbc","resolution":{"observed_at":"2026-05-10T11:10:09.035135Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.06610","last_updated":"2026-05-08T10:28:18Z","snapshot_observed_at":"2026-07-06T23:19:05.764765Z","submitted_at":"2026-05-07T17:28:40Z","title":"SoftSAE: Dynamic Top-K Selection for Adaptive Sparse Autoencoders","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T12:16:18.696425Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.06610"},"observation_digest":"sha256:50993590c2429f7ef3880c122201b63a89c99148e8edbb137613c205e2d4b963","observation_id":"e3291396-ee2c-47c2-adc0-889f23c5399d","resolution":{"observed_at":"2026-05-11T19:21:07.266346Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.06610","last_updated":"2026-05-08T10:28:18Z","snapshot_observed_at":"2026-07-06T23:19:05.764765Z","submitted_at":"2026-05-07T17:28:40Z","title":"SoftSAE: Dynamic Top-K Selection for Adaptive Sparse Autoencoders","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-11T01:57:20.566117Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.06610"},"observation_digest":"sha256:ec3ddce6662dc8d49caad77b0953b4fa0e87fd698138f2bfb9e0aa4bf515c702","observation_id":"44818334-549f-4973-ae27-627c14051897","resolution":{"observed_at":"2026-05-11T04:05:57.866804Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.08218","last_updated":"2026-05-06T13:21:24Z","snapshot_observed_at":"2026-08-02T13:46:49.241684Z","submitted_at":"2026-05-06T13:21:24Z","title":"Deep Dreams Are Made of This: Visualizing Monosemantic Features in Diffusion Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-12T01:18:05.476147Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.08218"},"observation_digest":"sha256:918dedcd2f9955698706124dd3670a6c569b7859f7e091992bb8f7896bf74f68","observation_id":"ebe358df-98fe-4d35-b345-07b9ee215e6f","resolution":{"observed_at":"2026-05-12T08:06:29.412743Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.10198","last_updated":"2026-05-11T08:46:29Z","snapshot_observed_at":"2026-07-06T23:22:13.774652Z","submitted_at":"2026-05-11T08:46:29Z","title":"Empty SPACE: Cross-Attention Sparsity for Concept Erasure in Diffusion Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-12T03:19:54.048685Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.10198"},"observation_digest":"sha256:95b795c18997f7839e5686450a1b34980dd105914b78c2b545af14d2eaa41c19","observation_id":"471f2e98-a29d-4dc2-ae75-e44bbf38ec57","resolution":{"observed_at":"2026-05-12T03:21:18.789700Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.15737","last_updated":"2026-05-15T08:46:02Z","snapshot_observed_at":"2026-07-06T23:27:01.213106Z","submitted_at":"2026-05-15T08:46:02Z","title":"BARRIER: Bounded Activation Regions for Robust Information Erasure","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-20T19:14:08.601508Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.15737"},"observation_digest":"sha256:6ca48b632c7b875761adabb4c54114b1217220220775ae978bed10f36083b581","observation_id":"bca5dd57-752e-454b-b251-5194271c8447","resolution":{"observed_at":"2026-05-20T19:18:54.704775Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.18719","last_updated":"2026-05-18T17:50:04Z","snapshot_observed_at":"2026-08-03T04:40:08.919496Z","submitted_at":"2026-05-18T17:50:04Z","title":"SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-05-20T11:26:55.810822Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.18719"},"observation_digest":"sha256:3c09644c21c0bfb9edce9bd0a98d7353374cb7a6b3fa0bf410b5b86d6aea86d1","observation_id":"da549611-49f1-4741-988a-0ffb9b8e4482","resolution":{"observed_at":"2026-05-20T11:28:14.345563Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.19739","last_updated":"2026-05-25T09:07:55Z","snapshot_observed_at":"2026-08-01T10:43:34.293585Z","submitted_at":"2026-05-19T12:10:09Z","title":"FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-20T05:27:47.218349Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.19739"},"observation_digest":"sha256:9363fe55970004b33410958d8b11e2454afa3ae1f128065dd178f73f78d8d648","observation_id":"bf1ea455-b0dc-4159-9aca-b695d2365d6d","resolution":{"observed_at":"2026-05-20T05:28:04.264363Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":"2501.18052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-07-01T15:05:47.561630Z","title":"Saeuron: Interpretable concept unlearning in diffusion models with sparse autoencoders","venue":null,"work_id":"8c3a56ae-640d-430d-8e59-87f754769833","year":2025},"citing_paper":{"arxiv_id":"2605.19739","last_updated":"2026-05-25T09:07:55Z","snapshot_observed_at":"2026-08-01T10:43:34.293585Z","submitted_at":"2026-05-19T12:10:09Z","title":"FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-30T18:18:15.772860Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2605.19739"},"observation_digest":"sha256:dc5d620c7d34c2e674872b3103153b5c7389210a6bbda0215e6512971b17bf97","observation_id":"bb8d1bd4-a117-43a4-826d-069b426c9cc2","resolution":{"observed_at":"2026-07-01T15:05:47.563104Z","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":"2501.18052","last_updated":"2025-05-21T21:35:16Z","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18052","snapshot_observed_at":"2026-08-01T17:08:24.028499Z","title":"arXiv:2501.18052 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17770","last_updated":"2026-07-20T10:03:37Z","snapshot_observed_at":"2026-08-07T07:11:07.475631Z","submitted_at":"2026-07-20T10:03:37Z","title":"Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T17:08:24.028499Z"},"links":{"cited_paper":"/paper/2501.18052","citing_paper":"/paper/2607.17770"},"observation_digest":"sha256:d4a6501f30c373dff74257d410c11be9ed58f6bff7d9f667c7f671b30aebd9e3","observation_id":"1cce40c1-227f-443d-b253-7959af414a22","resolution":{"observed_at":"2026-08-01T17:08:24.028499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2501.18052/citation-record","integrity":"/paper/2501.18052/integrity","json":"/paper/2501.18052/citation-record.json","paper":"/paper/2501.18052"},"outbound":[],"paper":{"arxiv_id":"2501.18052","last_updated":"2025-05-21T21:35:16Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T20:28:09.807683Z","submitted_at":"2025-01-29T23:29:47Z","title":"SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders"},"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 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2501.18052."}