{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WCHWDGAHJMIX3JZRTMMXCGT6RV","short_pith_number":"pith:WCHWDGAH","schema_version":"1.0","canonical_sha256":"b08f6198074b117da7319b19711a7e8d48347f5b77091d07312469a570d87de6","source":{"kind":"arxiv","id":"2606.25234","version":1},"attestation_state":"computed","paper":{"title":"Structuring Sparsity: Block-Sparse Featurizers Capture Visual Concept Manifolds","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aiden Swann, Atticus Geiger, Can Rager, Curt Tigges, Daniel Wurgaft, Dron Hazra, Ekdeep Singh Lubana, Fenil Doshi, Jack Merullo, Lee Sharkey, Lucius Bushnaq, Matthew Kowal, Michael Pearce, Mozes Jacobs, Nick Cammarata, Owen Lewis, Satchel Grant, Siddharth Boppana, Tal Haklay, Thomas Fel, Thomas Icard, Thomas McGrath, Thomas Serre, Usha Bhalla, Vasudev Shyam","submitted_at":"2026-06-23T23:28:30Z","abstract_excerpt":"What is the geometry of a visual percept? The most widely used protocols for decomposing neural network representations into interpretable parts treat concepts as isolated directions, yet recent work shows that concepts are often realized as geometric structures in low dimensional regions of activation space. We turn to the literature of Structured sparsity to close this gap, and show that block sparsity, which groups directions into blocks, is the prior matched to a generative model in which a representation is a sparse sum of low-dimensional manifolds: the modern, learned form of a classical"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.25234","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-23T23:28:30Z","cross_cats_sorted":[],"title_canon_sha256":"5ad7ae01d71cd4805490fe924c88efbab1cf57c8236360de2b779e8ad5ed9cf5","abstract_canon_sha256":"7fc5eb337e19a22bca0b2c8b190a3ae978afd6da6c5a660e620c608d442176a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T00:18:21.729309Z","signature_b64":"ad+lf9uoY+EN2folYdJIiGy8GxA65v7eByV1/N2SADqGHW7iJ+332hVuFcOZ2K7Q0nWgExOnC5viRUPtIgOoAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b08f6198074b117da7319b19711a7e8d48347f5b77091d07312469a570d87de6","last_reissued_at":"2026-06-25T00:18:21.728789Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T00:18:21.728789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structuring Sparsity: Block-Sparse Featurizers Capture Visual Concept Manifolds","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aiden Swann, Atticus Geiger, Can Rager, Curt Tigges, Daniel Wurgaft, Dron Hazra, Ekdeep Singh Lubana, Fenil Doshi, Jack Merullo, Lee Sharkey, Lucius Bushnaq, Matthew Kowal, Michael Pearce, Mozes Jacobs, Nick Cammarata, Owen Lewis, Satchel Grant, Siddharth Boppana, Tal Haklay, Thomas Fel, Thomas Icard, Thomas McGrath, Thomas Serre, Usha Bhalla, Vasudev Shyam","submitted_at":"2026-06-23T23:28:30Z","abstract_excerpt":"What is the geometry of a visual percept? The most widely used protocols for decomposing neural network representations into interpretable parts treat concepts as isolated directions, yet recent work shows that concepts are often realized as geometric structures in low dimensional regions of activation space. We turn to the literature of Structured sparsity to close this gap, and show that block sparsity, which groups directions into blocks, is the prior matched to a generative model in which a representation is a sparse sum of low-dimensional manifolds: the modern, learned form of a classical"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25234","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.25234/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.25234","created_at":"2026-06-25T00:18:21.728854+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.25234v1","created_at":"2026-06-25T00:18:21.728854+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25234","created_at":"2026-06-25T00:18:21.728854+00:00"},{"alias_kind":"pith_short_12","alias_value":"WCHWDGAHJMIX","created_at":"2026-06-25T00:18:21.728854+00:00"},{"alias_kind":"pith_short_16","alias_value":"WCHWDGAHJMIX3JZR","created_at":"2026-06-25T00:18:21.728854+00:00"},{"alias_kind":"pith_short_8","alias_value":"WCHWDGAH","created_at":"2026-06-25T00:18:21.728854+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV","json":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV.json","graph_json":"https://pith.science/api/pith-number/WCHWDGAHJMIX3JZRTMMXCGT6RV/graph.json","events_json":"https://pith.science/api/pith-number/WCHWDGAHJMIX3JZRTMMXCGT6RV/events.json","paper":"https://pith.science/paper/WCHWDGAH"},"agent_actions":{"view_html":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV","download_json":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV.json","view_paper":"https://pith.science/paper/WCHWDGAH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.25234&json=true","fetch_graph":"https://pith.science/api/pith-number/WCHWDGAHJMIX3JZRTMMXCGT6RV/graph.json","fetch_events":"https://pith.science/api/pith-number/WCHWDGAHJMIX3JZRTMMXCGT6RV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV/action/storage_attestation","attest_author":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV/action/author_attestation","sign_citation":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV/action/citation_signature","submit_replication":"https://pith.science/pith/WCHWDGAHJMIX3JZRTMMXCGT6RV/action/replication_record"}},"created_at":"2026-06-25T00:18:21.728854+00:00","updated_at":"2026-06-25T00:18:21.728854+00:00"}