{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:W7BWHKPSW6VDLFQJZD4CZHFZU4","short_pith_number":"pith:W7BWHKPS","schema_version":"1.0","canonical_sha256":"b7c363a9f2b7aa359609c8f82c9cb9a7012bacf96c3bb4d8da6727c5bb644dfb","source":{"kind":"arxiv","id":"2512.08048","version":3},"attestation_state":"computed","paper":{"title":"Family Matters: A Systematic Study of Spatial vs. Frequency Masking for Continual Test-Time Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chandler Timm C. Doloriel, Fadi Al Machot, Habib Ullah, Kristian Hovde Liland, Muhammad salman siddiqui, Taki Hasan Rafi, Tor Kristian Stevik, Yeonguk Yu, Yunbei Zhang","submitted_at":"2025-12-08T21:16:44Z","abstract_excerpt":"Recent continual test-time adaptation (CTTA) methods adopt masked image modeling to stabilize learning under distribution shift, yet each treats its masking family F as a fixed design choice and innovates exclusively along the selection strategy S, leaving the family axis underexplored. We present a systematic empirical study that isolates this axis. Using a controlled CTTA instantiation -- Mask to Adapt (M2A) -- that fixes S = random and standard losses, we vary only F across spatial (patch, pixel) and frequency (all-band, low-band, high-band) families while keeping every other component iden"},"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":"2512.08048","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-12-08T21:16:44Z","cross_cats_sorted":[],"title_canon_sha256":"2435e9d09613537920b03af8f8c675a7a0fa64cba345a87153847beb65461853","abstract_canon_sha256":"4c9a7c0b12c2b332550e29ec0a26ae80ea25fd586d526e493cb40cf2297cdceb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:03:39.453849Z","signature_b64":"0OvLWNDJR/WL7pUFm0ccAN1H5mGGgwGmzezqPm4FqTXznQBByInj2SNBOFggda7Jh4UjQXJpKzk3wvjTPnm2Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7c363a9f2b7aa359609c8f82c9cb9a7012bacf96c3bb4d8da6727c5bb644dfb","last_reissued_at":"2026-06-02T01:03:39.453360Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:03:39.453360Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Family Matters: A Systematic Study of Spatial vs. Frequency Masking for Continual Test-Time Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chandler Timm C. Doloriel, Fadi Al Machot, Habib Ullah, Kristian Hovde Liland, Muhammad salman siddiqui, Taki Hasan Rafi, Tor Kristian Stevik, Yeonguk Yu, Yunbei Zhang","submitted_at":"2025-12-08T21:16:44Z","abstract_excerpt":"Recent continual test-time adaptation (CTTA) methods adopt masked image modeling to stabilize learning under distribution shift, yet each treats its masking family F as a fixed design choice and innovates exclusively along the selection strategy S, leaving the family axis underexplored. We present a systematic empirical study that isolates this axis. Using a controlled CTTA instantiation -- Mask to Adapt (M2A) -- that fixes S = random and standard losses, we vary only F across spatial (patch, pixel) and frequency (all-band, low-band, high-band) families while keeping every other component iden"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2512.08048","kind":"arxiv","version":3},"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/2512.08048/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":"2512.08048","created_at":"2026-06-02T01:03:39.453423+00:00"},{"alias_kind":"arxiv_version","alias_value":"2512.08048v3","created_at":"2026-06-02T01:03:39.453423+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.08048","created_at":"2026-06-02T01:03:39.453423+00:00"},{"alias_kind":"pith_short_12","alias_value":"W7BWHKPSW6VD","created_at":"2026-06-02T01:03:39.453423+00:00"},{"alias_kind":"pith_short_16","alias_value":"W7BWHKPSW6VDLFQJ","created_at":"2026-06-02T01:03:39.453423+00:00"},{"alias_kind":"pith_short_8","alias_value":"W7BWHKPS","created_at":"2026-06-02T01:03:39.453423+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/W7BWHKPSW6VDLFQJZD4CZHFZU4","json":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4.json","graph_json":"https://pith.science/api/pith-number/W7BWHKPSW6VDLFQJZD4CZHFZU4/graph.json","events_json":"https://pith.science/api/pith-number/W7BWHKPSW6VDLFQJZD4CZHFZU4/events.json","paper":"https://pith.science/paper/W7BWHKPS"},"agent_actions":{"view_html":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4","download_json":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4.json","view_paper":"https://pith.science/paper/W7BWHKPS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2512.08048&json=true","fetch_graph":"https://pith.science/api/pith-number/W7BWHKPSW6VDLFQJZD4CZHFZU4/graph.json","fetch_events":"https://pith.science/api/pith-number/W7BWHKPSW6VDLFQJZD4CZHFZU4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4/action/storage_attestation","attest_author":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4/action/author_attestation","sign_citation":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4/action/citation_signature","submit_replication":"https://pith.science/pith/W7BWHKPSW6VDLFQJZD4CZHFZU4/action/replication_record"}},"created_at":"2026-06-02T01:03:39.453423+00:00","updated_at":"2026-06-02T01:03:39.453423+00:00"}