{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:YK5APSKS4HD7QBPMDN2GCFMG5M","short_pith_number":"pith:YK5APSKS","schema_version":"1.0","canonical_sha256":"c2ba07c952e1c7f805ec1b74611586eb258b5915d89727ffbc4794f753372e97","source":{"kind":"arxiv","id":"2606.31676","version":1},"attestation_state":"computed","paper":{"title":"REDI: Corpus Aware Patch Ranking for DINOv3 Token Reduction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chanjong Im, Sebastian Diem, Thomas Mandl","submitted_at":"2026-06-30T13:54:40Z","abstract_excerpt":"Most token reduction methods for Vision Transformers seek favorable tradeoffs between accuracy and efficiency by pruning, merging, or pooling patch tokens. REDI (Relevance for DINOv3 Token Reduction) studies this question through a controlled supervised reference: how should a fixed token budget be allocated across patches for image classification? REDI quantizes final block DINOv3 patch representations into a visual vocabulary and derives class conditioned corpus scores using supervised TF-IDF over visual words. For each validation image, the ground truth class selects a row of the TF-IDF tab"},"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":"2606.31676","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-30T13:54:40Z","cross_cats_sorted":[],"title_canon_sha256":"fb7a85eaa0145f8b4e16f552124b5bafa4469df248dcecf24681a04a9af2d0ac","abstract_canon_sha256":"8c4c4b3cc6c9ff5a2070bc59f999790213a75b47417a23f1ef5a0b1919c996d1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-01T01:18:11.373754Z","signature_b64":"U0HhqmefBEEg0o4s2gVJ3QnXJir+GyRSJ3tudFF64lDKwZetQ0uOc9JE/PA873XXeVib0o/ZDOXQpOGhJX9XAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2ba07c952e1c7f805ec1b74611586eb258b5915d89727ffbc4794f753372e97","last_reissued_at":"2026-07-01T01:18:11.373249Z","signature_status":"signed_v1","first_computed_at":"2026-07-01T01:18:11.373249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"REDI: Corpus Aware Patch Ranking for DINOv3 Token Reduction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chanjong Im, Sebastian Diem, Thomas Mandl","submitted_at":"2026-06-30T13:54:40Z","abstract_excerpt":"Most token reduction methods for Vision Transformers seek favorable tradeoffs between accuracy and efficiency by pruning, merging, or pooling patch tokens. REDI (Relevance for DINOv3 Token Reduction) studies this question through a controlled supervised reference: how should a fixed token budget be allocated across patches for image classification? REDI quantizes final block DINOv3 patch representations into a visual vocabulary and derives class conditioned corpus scores using supervised TF-IDF over visual words. For each validation image, the ground truth class selects a row of the TF-IDF tab"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.31676","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/2606.31676/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":"2606.31676","created_at":"2026-07-01T01:18:11.373306+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.31676v1","created_at":"2026-07-01T01:18:11.373306+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.31676","created_at":"2026-07-01T01:18:11.373306+00:00"},{"alias_kind":"pith_short_12","alias_value":"YK5APSKS4HD7","created_at":"2026-07-01T01:18:11.373306+00:00"},{"alias_kind":"pith_short_16","alias_value":"YK5APSKS4HD7QBPM","created_at":"2026-07-01T01:18:11.373306+00:00"},{"alias_kind":"pith_short_8","alias_value":"YK5APSKS","created_at":"2026-07-01T01:18:11.373306+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/YK5APSKS4HD7QBPMDN2GCFMG5M","json":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M.json","graph_json":"https://pith.science/api/pith-number/YK5APSKS4HD7QBPMDN2GCFMG5M/graph.json","events_json":"https://pith.science/api/pith-number/YK5APSKS4HD7QBPMDN2GCFMG5M/events.json","paper":"https://pith.science/paper/YK5APSKS"},"agent_actions":{"view_html":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M","download_json":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M.json","view_paper":"https://pith.science/paper/YK5APSKS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.31676&json=true","fetch_graph":"https://pith.science/api/pith-number/YK5APSKS4HD7QBPMDN2GCFMG5M/graph.json","fetch_events":"https://pith.science/api/pith-number/YK5APSKS4HD7QBPMDN2GCFMG5M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M/action/storage_attestation","attest_author":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M/action/author_attestation","sign_citation":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M/action/citation_signature","submit_replication":"https://pith.science/pith/YK5APSKS4HD7QBPMDN2GCFMG5M/action/replication_record"}},"created_at":"2026-07-01T01:18:11.373306+00:00","updated_at":"2026-07-01T01:18:11.373306+00:00"}