{"as_of":"2026-08-10T06:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cd2a7b9bda8f24bbe63e796cada8dbbc31a021e8218d9eecfc276be20e92894f","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":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":48,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:43:15.410159Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-07T14:43:15.410159Z","title":"Learning Multi - Level Features with Matryoshka Sparse Autoencoders","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18235","last_updated":"2025-05-23T13:31:22Z","snapshot_observed_at":"2026-08-08T23:48:03.598388Z","submitted_at":"2025-05-23T13:31:22Z","title":"The Origins of Representation Manifolds in Large Language Models","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T14:43:15.410159Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2505.18235"},"observation_digest":"sha256:06e26cb3f3085756f520f5e6323066f64874700f6c5a57d63f2a669db2b379e9","observation_id":"dfd3766a-5b5b-4a41-998c-1079183e7dfb","resolution":{"observed_at":"2026-08-07T14:43:15.410159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-07T14:02:59.051713Z","title":"Learning multi-level features with matryoshka sparse autoencoders.arXiv preprint arXiv:2503.17547, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20254","last_updated":"2025-05-26T17:31:36Z","snapshot_observed_at":"2026-08-08T03:52:01.664959Z","submitted_at":"2025-05-26T17:31:36Z","title":"Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:02:59.051713Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2505.20254"},"observation_digest":"sha256:e0d8fb9a3fb34a2d4391fda9c13c19bfc53c50be4fd571b231e89a7f9e6d5e12","observation_id":"4f48c707-9311-4ae1-a416-49bbd095833e","resolution":{"observed_at":"2026-08-07T14:02:59.051713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-07T13:41:57.359666Z","title":"Learning multi-level features with matryoshka sparse autoencoders","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.21399","last_updated":"2025-05-27T16:24:02Z","snapshot_observed_at":"2026-08-09T17:19:27.700339Z","submitted_at":"2025-05-27T16:24:02Z","title":"Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T13:41:57.359666Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2505.21399"},"observation_digest":"sha256:d1252a115c2841e5fff85c708ac4c2b8bac145a9c5d63c85f290f4f3d33a705b","observation_id":"ac1a8290-6e72-4e91-b7c7-0be9661cf1d1","resolution":{"observed_at":"2026-08-07T13:41:57.359666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-07T12:35:25.410836Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.24473","last_updated":"2025-06-05T11:42:24Z","snapshot_observed_at":"2026-08-09T06:27:07.999203Z","submitted_at":"2025-05-30T11:20:44Z","title":"Train One Sparse Autoencoder Across Multiple Sparsity Budgets to Preserve Interpretability and Accuracy","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T12:35:25.410836Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2505.24473"},"observation_digest":"sha256:22da08d442dbcac29ad0ecf2afa8b07bb7aaa0d35c7c05546a8048662950af6c","observation_id":"50c042c0-98a9-45b1-80ca-1b9e07b552cf","resolution":{"observed_at":"2026-08-07T12:35:25.410836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-07T11:56:15.148684Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01197","last_updated":"2025-06-01T22:20:07Z","snapshot_observed_at":"2026-08-08T11:50:05.971005Z","submitted_at":"2025-06-01T22:20:07Z","title":"Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T11:56:15.148684Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2506.01197"},"observation_digest":"sha256:e0cc9bbdd42b24cdd8286388d123429693ba7d4125251a6f0505d332b9308918","observation_id":"988e5cf1-f642-444d-b522-b722a0b3931b","resolution":{"observed_at":"2026-08-07T11:56:15.148684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-06T17:46:16.512841Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders , 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.10106","last_updated":"2025-07-14T09:45:34Z","snapshot_observed_at":"2026-08-07T07:18:38.132008Z","submitted_at":"2025-07-14T09:45:34Z","title":"BlueGlass: A Framework for Composite AI Safety","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T17:46:16.512841Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2507.10106"},"observation_digest":"sha256:10101111a3020830f0301a50523c27b9f2cdfa2c93acc08939faa5dbdef1324e","observation_id":"10b64f59-8fbe-4986-b96d-8f7e92bc671d","resolution":{"observed_at":"2026-08-06T17:46:16.512841Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-06T16:40:41.151327Z","title":"Learning Multi - Level Features with Matryoshka Sparse Autoencoders , March 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.12950","last_updated":"2025-07-18T09:19:19Z","snapshot_observed_at":"2026-08-08T08:02:10.889574Z","submitted_at":"2025-07-17T09:43:20Z","title":"Insights into a radiology-specialised multimodal large language model with sparse autoencoders","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T16:40:41.151327Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2507.12950"},"observation_digest":"sha256:911808cb3f19842fa7553322d76874edab1c07ea642444d9ecf6351840ebfaea","observation_id":"ae2e7e69-ddb3-45ce-9d79-37508d945371","resolution":{"observed_at":"2026-08-06T16:40:41.151327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T17:18:54.254819Z","title":"Learning multi-level features with matryoshka sparse autoencoders.arXiv preprint arXiv:2503.17547,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.16560","last_updated":"2026-07-07T00:22:17Z","snapshot_observed_at":"2026-08-09T16:18:10.268970Z","submitted_at":"2025-08-22T17:26:33Z","title":"Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders","version":4},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T17:18:54.254819Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2508.16560"},"observation_digest":"sha256:ded056e9567be13fa7741a04db0abf32f890899adbdf96a6d531847dbfc72a91","observation_id":"dd93be14-1c3c-4914-b46a-4a3b389dff4b","resolution":{"observed_at":"2026-08-05T17:18:54.254819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T18:47:45.260976Z","title":"& Nanda, N","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.18235","last_updated":"2025-08-20T00:57:21Z","snapshot_observed_at":"2026-08-05T18:44:01.835548Z","submitted_at":"2025-08-20T00:57:21Z","title":"Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T18:47:45.260976Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2508.18235"},"observation_digest":"sha256:34295050b3f072ab0a5cc78a514f27e9ddbd13d17b14816ca318c095b2f58691","observation_id":"8a58229d-fb4e-4aa8-8b74-8d83bd295050","resolution":{"observed_at":"2026-08-05T18:47:45.260976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2509.18127","last_updated":"2026-04-14T10:00:44Z","snapshot_observed_at":"2026-08-02T17:25:00.233548Z","submitted_at":"2025-09-11T11:22:43Z","title":"Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-18T18:13:01.662828Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2509.18127"},"observation_digest":"sha256:fe8aa2ba4553313335659a5446d282de24fddc2bcd5a495a7a31634e262a0289","observation_id":"2c4f7495-47a9-48a4-a50d-a1c8e379146f","resolution":{"observed_at":"2026-05-18T18:16:43.795195Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-04T15:20:32.122570Z","title":"Learning multi-level features with matryoshka sparse autoencoders","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.122570Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:61de0da7011f8015368f093ce996f38abd317c22bb48954f98b25bd1f380e1a8","observation_id":"7a8ad517-1171-4701-8618-4be505441825","resolution":{"observed_at":"2026-08-04T15:20:32.122570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-03T18:21:10.192574Z","title":"doi: 10.1084/jem.20210281","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.05794","last_updated":"2026-05-26T15:50:47Z","snapshot_observed_at":"2026-08-08T06:20:44.964192Z","submitted_at":"2025-12-05T15:18:50Z","title":"Mechanistic Interpretability of Antibody Language Models Using SAEs","version":3},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T18:21:10.192574Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2512.05794"},"observation_digest":"sha256:8a417b155695c92325d0c95f5174e07c9000e8fa8626f2592f4c8f9a565b28d5","observation_id":"0349ddfd-a514-451c-9bfa-85a6ee2afee6","resolution":{"observed_at":"2026-08-03T18:21:10.192574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-03T05:48:08.046788Z","title":"Bussmann, B., Nabeshima, N., Karvonen, A., and Nanda, N","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2602.01322","last_updated":"2026-05-25T13:47:55Z","snapshot_observed_at":"2026-08-03T05:48:06.509566Z","submitted_at":"2026-02-01T16:34:45Z","title":"PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T05:48:08.046788Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2602.01322"},"observation_digest":"sha256:07819409ef0eb569fb7ea0671a40f1cfe05cb9dd87eeb215ec32d4c155e3b309","observation_id":"f9a389fd-ec55-4b82-bf1f-d86919984c36","resolution":{"observed_at":"2026-08-03T05:48:08.046788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-02T18:56:20.402722Z","title":"Aaron Maiwald, Piotr Jedryszek, Florent Draye, Garrett M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.04198","last_updated":"2026-06-16T16:00:25Z","snapshot_observed_at":"2026-08-09T04:08:36.721770Z","submitted_at":"2026-03-04T15:46:23Z","title":"Stable and Steerable Sparse Autoencoders with Weight Regularization","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T18:56:20.402722Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2603.04198"},"observation_digest":"sha256:ddf4f6adfb2f6f1b7927c5677e6e2895764cdaee96b3b52b9f3a7eeadd8d837c","observation_id":"ade5bafd-71bb-4827-a4e3-777439b4889c","resolution":{"observed_at":"2026-08-02T18:56:20.402722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2604.06495","last_updated":"2026-04-07T21:56:23Z","snapshot_observed_at":"2026-07-06T22:54:57.597183Z","submitted_at":"2026-04-07T21:56:23Z","title":"Improving Robustness In Sparse Autoencoders via Masked Regularization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T18:47:15.830063Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2604.06495"},"observation_digest":"sha256:836d1a0f24d181297bb3a370d355a31d185df81c5872ad89696897437bfa1ad5","observation_id":"54b3f94b-a4ce-461d-ae04-256f59d7ed20","resolution":{"observed_at":"2026-05-10T23:55:51.694717Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2604.08846","last_updated":"2026-04-10T01:01:56Z","snapshot_observed_at":"2026-08-02T14:54:38.934183Z","submitted_at":"2026-04-10T01:01:56Z","title":"Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T18:04:05.157103Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2604.08846"},"observation_digest":"sha256:8833d11ea30a6c67ab723a0ee006db6918d6520296a7f73c768e6c140f6e8afe","observation_id":"7d293bf9-e144-4fcf-9ca0-d8fdde9a88ca","resolution":{"observed_at":"2026-05-11T05:35:57.369684Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2604.21511","last_updated":"2026-05-31T10:24:45Z","snapshot_observed_at":"2026-08-01T16:15:18.472062Z","submitted_at":"2026-04-23T10:13:21Z","title":"From Tokens to Concepts: Leveraging SAE for SPLADE","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-09T20:29:51.212006Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2604.21511"},"observation_digest":"sha256:7fba39cdda88f14df4c21195cc36f34d5b1a4c1a3563edc2d015e5c2d1c1e64b","observation_id":"ba62daa4-e5e8-4f4c-9eef-566affe5ee70","resolution":{"observed_at":"2026-05-11T15:11:07.816562Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2604.21511","last_updated":"2026-05-31T10:24:45Z","snapshot_observed_at":"2026-08-01T16:15:18.472062Z","submitted_at":"2026-04-23T10:13:21Z","title":"From Tokens to Concepts: Leveraging SAE for SPLADE","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-04T23:24:54.636140Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2604.21511"},"observation_digest":"sha256:12c841d9efa87a922210c93d2285a2fa32c9f5fee409c1292bb01c5a6b4da784","observation_id":"e57f8934-c8c5-4bd3-876e-c60283122d21","resolution":{"observed_at":"2026-07-04T23:30:12.038645Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.07922","last_updated":"2026-05-11T02:18:14Z","snapshot_observed_at":"2026-07-06T23:20:15.696237Z","submitted_at":"2026-05-08T15:57:37Z","title":"Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-11T03:13:58.543525Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.07922"},"observation_digest":"sha256:d3fa0143f24109bf5459ff019649e5e3634491c05daeb1e17845b88d5dfe5ec9","observation_id":"9a842034-6079-415b-b9c7-dd8349be1e47","resolution":{"observed_at":"2026-05-11T03:15:54.324345Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.07922","last_updated":"2026-05-11T02:18:14Z","snapshot_observed_at":"2026-07-06T23:20:15.696237Z","submitted_at":"2026-05-08T15:57:37Z","title":"Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-12T03:35:50.776347Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.07922"},"observation_digest":"sha256:eeb706352ac2a8d7f66355647818d0ff228b04dbdb42f5e97565e696fcbacbde","observation_id":"2ef61865-a337-4a47-8efc-dd15032e932a","resolution":{"observed_at":"2026-05-12T07:16:25.309504Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.09967","last_updated":"2026-05-11T04:18:43Z","snapshot_observed_at":"2026-07-06T23:21:59.096464Z","submitted_at":"2026-05-11T04:18:43Z","title":"Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-12T03:31:40.195348Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.09967"},"observation_digest":"sha256:e806f74887a9788032dfd886a94ce7c602ba38fbfe9cefcec0ddfd53d8360ed4","observation_id":"c308cd1a-c6c9-4d08-8174-c8c08ee1d91a","resolution":{"observed_at":"2026-05-12T07:16:30.283057Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12055","last_updated":"2026-05-14T07:07:27Z","snapshot_observed_at":"2026-07-31T12:10:28.537993Z","submitted_at":"2026-05-12T12:37:06Z","title":"Do Language Models Encode Knowledge of Linguistic Constraint Violations?","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T06:24:16.157548Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12055"},"observation_digest":"sha256:30c7cbe313c8aeafde38e0fe2884cb665878ac1a9decba4c492d9829027f41f0","observation_id":"4535f8b1-44e4-43b3-be19-a86ad1d49825","resolution":{"observed_at":"2026-05-13T06:27:24.757936Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12055","last_updated":"2026-05-14T07:07:27Z","snapshot_observed_at":"2026-07-31T12:10:28.537993Z","submitted_at":"2026-05-12T12:37:06Z","title":"Do Language Models Encode Knowledge of Linguistic Constraint Violations?","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-15T05:44:52.491280Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12055"},"observation_digest":"sha256:0b39ab70a02ff0a672ebe932ec69f32ca6daaebf3366c64ad1eb01c149fb088e","observation_id":"85f509fb-4327-4872-b295-db4d6f68327a","resolution":{"observed_at":"2026-05-15T05:45:05.715255Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-14T20:53:40.666929Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:62fa4d19832ec49ef7d7be5ad386c65319e62aa8453af51210652ee7f42c2d57","observation_id":"4212971a-d40a-4f76-add1-5c3847628cf5","resolution":{"observed_at":"2026-05-14T20:59:28.815697Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-15T04:59:11.877068Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:55da5e4b096f6ec599c5a3b9809e4cdee4c116a66ad5c1e2c760bd71ba347ac0","observation_id":"050f8176-bb23-4cb4-9104-f83203f5186e","resolution":{"observed_at":"2026-05-15T04:59:45.210865Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":3},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-20T21:49:47.934339Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:9084d37b2fe202b1f028bf6109716155b32a3700208d50dd64233253fbd7ec9d","observation_id":"5d789e60-1136-4590-985d-75bb3bca272d","resolution":{"observed_at":"2026-05-20T21:53:47.204449Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12770","last_updated":"2026-05-19T21:54:38Z","snapshot_observed_at":"2026-07-06T23:24:23.402304Z","submitted_at":"2026-05-12T21:32:45Z","title":"WriteSAE: Sparse Autoencoders for Recurrent State","version":4},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T07:46:41.159688Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12770"},"observation_digest":"sha256:17b34e4c704c5cddeb0853abf67b2f09af0d2cf366c99780832c77db10e8ffcb","observation_id":"538895f4-9bdb-4016-bc9d-a3bd480da609","resolution":{"observed_at":"2026-05-21T07:49:50.149450Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.12874","last_updated":"2026-05-13T01:41:38Z","snapshot_observed_at":"2026-07-06T23:24:32.412966Z","submitted_at":"2026-05-13T01:41:38Z","title":"Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-14T20:27:38.363693Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.12874"},"observation_digest":"sha256:18c20cd76a26ba0b5b2719e4a847fa44ff5808d776fd77d7c981045f90bfa8a0","observation_id":"73bbb688-d283-4122-9be1-700e48d61927","resolution":{"observed_at":"2026-05-14T20:27:58.925563Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.14694","last_updated":"2026-05-14T11:10:52Z","snapshot_observed_at":"2026-08-07T16:34:09.292629Z","submitted_at":"2026-05-14T11:10:52Z","title":"The Rate-Distortion-Polysemanticity Tradeoff in SAEs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-30T21:13:01.880935Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.14694"},"observation_digest":"sha256:5dd99a879661edaeb0adb6ef1bdee9c8dc58ad3b48e925567bbd0281ddf8cbc8","observation_id":"d94daa48-28f1-402c-bbaa-fe58c648ac45","resolution":{"observed_at":"2026-06-30T21:15:04.074818Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.18229","last_updated":"2026-05-18T11:20:57Z","snapshot_observed_at":"2026-08-09T07:08:46.312980Z","submitted_at":"2026-05-18T11:20:57Z","title":"Are Sparse Autoencoder Benchmarks Reliable?","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-20T12:43:13.014365Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.18229"},"observation_digest":"sha256:9710faa419dde1ff648069de9176d5be6ac8925b985ecdba737af65ecd033c3a","observation_id":"ef29cbe4-5fbc-4e64-8cdd-37a10931f375","resolution":{"observed_at":"2026-05-20T12:43:16.816953Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.18537","last_updated":"2026-05-18T15:20:35Z","snapshot_observed_at":"2026-08-02T17:57:51.032458Z","submitted_at":"2026-05-18T15:20:35Z","title":"Probing for Representation Manifolds in Superposition","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-05-20T11:46:34.184997Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.18537"},"observation_digest":"sha256:70ed6f34ea42676b3dad8089001c76234c8fa36a4eb75fb091e9dbaa99ba4a9a","observation_id":"f9ab20dc-5b04-44e6-96d4-3a87316872b0","resolution":{"observed_at":"2026-05-20T11:48:15.054342Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.20612","last_updated":"2026-05-26T15:25:51Z","snapshot_observed_at":"2026-07-06T23:31:08.671011Z","submitted_at":"2026-05-20T01:59:06Z","title":"Matryoshka Concept Bottleneck Models","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T18:02:47.654185Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.20612"},"observation_digest":"sha256:9d960fc9dd865db9a28373feeb5f2d70e1ded03e5fc84a149b96ddadf31af55a","observation_id":"1aa28f09-e98d-4638-8563-a6a8a45b07d2","resolution":{"observed_at":"2026-06-30T18:04:57.912098Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2605.28149","last_updated":"2026-08-04T06:19:42Z","snapshot_observed_at":"2026-08-07T23:09:28.260788Z","submitted_at":"2026-05-27T08:31:43Z","title":"Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-29T14:16:44.232080Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.28149"},"observation_digest":"sha256:612d28ed0da01cd323144a322e73378064343af8e9370cdf29f8fc635c6cd795","observation_id":"20488253-1250-4e39-92ef-a6aa019f498b","resolution":{"observed_at":"2026-06-29T14:23:30.768006Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-04T05:02:51.359419Z","title":"Learning multi-level features with matryoshka sparse autoencoders.arXiv preprint arXiv:2503.17547, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.28149","last_updated":"2026-08-04T06:19:42Z","snapshot_observed_at":"2026-08-07T23:09:28.260788Z","submitted_at":"2026-05-27T08:31:43Z","title":"Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T05:02:51.359419Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2605.28149"},"observation_digest":"sha256:df06072eed1dc53e14249c0311e926850ccfaad82cdcf56c4c8750d73573e151","observation_id":"afbcad70-c0ed-4f22-9375-fbd162d4110c","resolution":{"observed_at":"2026-08-04T05:02:51.359419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.06333","last_updated":"2026-06-04T16:08:25Z","snapshot_observed_at":"2026-08-02T07:30:20.394633Z","submitted_at":"2026-06-04T16:08:25Z","title":"Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-06-28T02:07:18.198225Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.06333"},"observation_digest":"sha256:b1f4c28c30e744c24a26375febd486a4a4462f47ec61e4e7e021b2d65f766681","observation_id":"cc41b531-7c3f-463f-8791-120635d82074","resolution":{"observed_at":"2026-06-28T02:11:29.051237Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.07654","last_updated":"2026-06-03T02:57:09Z","snapshot_observed_at":"2026-08-03T13:06:29.213397Z","submitted_at":"2026-06-03T02:57:09Z","title":"MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-06-28T06:59:06.801340Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.07654"},"observation_digest":"sha256:7e5160ae1cc0f9f4179477d8062e1eddf17fea010d021fbf7cdd96cd198f859a","observation_id":"85168b2f-b7ad-4caa-97bf-d31e57e4f8f9","resolution":{"observed_at":"2026-07-02T07:26:45.679414Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.10080","last_updated":"2026-06-08T18:54:31Z","snapshot_observed_at":"2026-07-06T23:49:17.868841Z","submitted_at":"2026-06-08T18:54:31Z","title":"VFUSE: Virulent Feature Understanding with Sparse autoEncoders","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-06-27T16:57:52.441415Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.10080"},"observation_digest":"sha256:bf89472becb35c5407002173dea1ba928dc51c0346fc1c223856cc567b047d81","observation_id":"aeadf5f0-deac-45d1-9fed-5caa5f84796c","resolution":{"observed_at":"2026-07-03T00:57:29.990683Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.11722","last_updated":"2026-06-10T06:53:58Z","snapshot_observed_at":"2026-08-02T23:00:11.313609Z","submitted_at":"2026-06-10T06:53:58Z","title":"ICA Lens: Interpreting Language Models Without Training Another Dictionary","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T10:21:58.878499Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.11722"},"observation_digest":"sha256:7519b2c5f89c514e1abb6584698d92c06222ab91405ddf2fa73d4ccf0964929d","observation_id":"aeb88284-f81f-4280-b1ef-a3b12b0169bb","resolution":{"observed_at":"2026-07-03T09:17:49.077422Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.12360","last_updated":"2026-06-10T17:31:16Z","snapshot_observed_at":"2026-07-06T23:51:17.719874Z","submitted_at":"2026-06-10T17:31:16Z","title":"Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal","version":1},"reference_index":245,"source":"arxiv_source","source_observed_at":"2026-06-27T10:32:57.295159Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.12360"},"observation_digest":"sha256:afdfd2d75b62739515ed0d566a817b775a2141a61f9edcdaa5084246199daf02","observation_id":"ff56213b-bead-4e9a-9612-d63740a43f46","resolution":{"observed_at":"2026-07-03T09:07:47.947301Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.14990","last_updated":"2026-06-16T02:02:24Z","snapshot_observed_at":"2026-08-10T00:03:17.939494Z","submitted_at":"2026-06-12T22:22:40Z","title":"Rational Sparse Autoencoder","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T04:29:27.383661Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.14990"},"observation_digest":"sha256:083efa1a25df87c7abca486fca6753fbba3ddbec746a2ad0b4547615e6e4cced","observation_id":"74f60525-2cdd-419e-8585-cb92693ab7d4","resolution":{"observed_at":"2026-07-03T17:08:43.960948Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.20347","last_updated":"2026-06-18T15:15:57Z","snapshot_observed_at":"2026-08-03T19:01:38.303561Z","submitted_at":"2026-06-18T15:15:57Z","title":"Critical Percolation as a Synthetic Data Model for Interpretability","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-26T17:41:29.317167Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.20347"},"observation_digest":"sha256:60fe25afaf5819730220f5565167fe99c25ffa45c3a04d04bd9a5f8e44081bba","observation_id":"0b41c211-49cd-45e5-9a40-b0e7ed98e96a","resolution":{"observed_at":"2026-07-04T03:49:29.645376Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.22994","last_updated":"2026-06-22T08:12:34Z","snapshot_observed_at":"2026-08-08T15:52:49.568637Z","submitted_at":"2026-06-22T08:12:34Z","title":"Do Sparse Autoencoders Learn Meaningful Concept Hierarchies?","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-26T08:46:48.220801Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.22994"},"observation_digest":"sha256:1454869aec71e20d50ab75d86ef486d8f4f11a8652a080d38160a5c3d503af2d","observation_id":"bc2e77cb-2669-4fcd-9876-9963fac35238","resolution":{"observed_at":"2026-07-04T10:29:45.362219Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.27321","last_updated":"2026-07-14T14:49:19Z","snapshot_observed_at":"2026-08-01T21:46:17.605652Z","submitted_at":"2026-06-25T17:34:39Z","title":"Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-26T05:01:55.327724Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.27321"},"observation_digest":"sha256:f9299ff8a84a31200510641b81d6a06f82e46c124ccfd9519967c98af27043dd","observation_id":"abe129d7-1364-4adf-a138-539e04a2db16","resolution":{"observed_at":"2026-07-04T13:39:50.936158Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-07-15T10:30:51.183063Z","title":"arXiv:2503.17547","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.27321","last_updated":"2026-07-14T14:49:19Z","snapshot_observed_at":"2026-08-01T21:46:17.605652Z","submitted_at":"2026-06-25T17:34:39Z","title":"Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-15T10:30:51.183063Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.27321"},"observation_digest":"sha256:19a19102b97546d87708a1ffb8f5192e4ca36eded638402b6c8a7c65bcce55c8","observation_id":"347c5b27-8d15-4393-b4b0-5a027fbf95d6","resolution":{"observed_at":"2026-07-15T10:30:51.183063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.28548","last_updated":"2026-06-26T19:07:34Z","snapshot_observed_at":"2026-07-07T00:02:38.226622Z","submitted_at":"2026-06-26T19:07:34Z","title":"Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T01:20:29.026464Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.28548"},"observation_digest":"sha256:60f73e099b15728f9416cd25d1340f388a25d729bcc4187902af2bc162acc266","observation_id":"f5910d1d-1615-4ca3-83de-1c75d4d5eebd","resolution":{"observed_at":"2026-07-01T15:35:48.366795Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.29341","last_updated":"2026-07-02T05:28:08Z","snapshot_observed_at":"2026-08-09T23:05:00.653021Z","submitted_at":"2026-06-28T11:16:12Z","title":"Monosemanticity in Recommender Systems","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-30T02:26:45.295182Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.29341"},"observation_digest":"sha256:6a62485cac4387cc5542c6edd705af0576c6758be9adb49ff4f414cb97b20434","observation_id":"ac712014-e362-469d-b601-5d72cfb819f4","resolution":{"observed_at":"2026-06-30T02:34:13.627523Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2606.29341","last_updated":"2026-07-02T05:28:08Z","snapshot_observed_at":"2026-08-09T23:05:00.653021Z","submitted_at":"2026-06-28T11:16:12Z","title":"Monosemanticity in Recommender Systems","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-03T22:47:21.810288Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2606.29341"},"observation_digest":"sha256:8f0512f74ffe531c1feb67cd01402d3202e89128642e78759d5fc631bb0db490","observation_id":"96fc9cef-3493-4c34-882d-f0b5b9ba7a35","resolution":{"observed_at":"2026-07-03T22:49:00.652630Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":"2503.17547","doi":"10.48550/arxiv.2503.17547","metadata_source":"arxiv_reference","pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, and Mohamed S","venue":"arXiv (Cornell University)","work_id":"b9ac82a0-61c3-4cc4-b425-1e959744df8b","year":2025},"citing_paper":{"arxiv_id":"2607.01799","last_updated":"2026-07-02T07:16:14Z","snapshot_observed_at":"2026-08-01T04:03:30.581540Z","submitted_at":"2026-07-02T07:16:14Z","title":"Expander Sparse Autoencoders: Parameter-Efficient Dictionaries for Mechanistic Interpretability","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-03T17:19:36.936483Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2607.01799"},"observation_digest":"sha256:4e33a885c721a2101f4c681f7551b40be0d4b4d1218e75af76cb8d6749d6994c","observation_id":"b17ebd3c-35dd-4b26-a41c-b9f4ace6dd43","resolution":{"observed_at":"2026-07-03T17:28:44.170293Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.17547/citation-record","integrity":"/paper/2503.17547/integrity","json":"/paper/2503.17547/citation-record.json","paper":"/paper/2503.17547"},"outbound":[],"paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka 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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 48 inbound Pith citation observations for arXiv:2503.17547."}