{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZJ7VYY7JEWAVGNEJLESJXTLOI7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"04fb3d90c250b5ae0f8e72104fe21c9682098c45cdf6ea758bf5809a42de723b","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T18:09:49Z","title_canon_sha256":"1acca5fbfbcb4726d85ad8a92e1178d912211236a0f6d223b380b63266652b3c"},"schema_version":"1.0","source":{"id":"2606.23825","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23825","created_at":"2026-06-24T00:14:27Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23825v1","created_at":"2026-06-24T00:14:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23825","created_at":"2026-06-24T00:14:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZJ7VYY7JEWAV","created_at":"2026-06-24T00:14:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZJ7VYY7JEWAVGNEJ","created_at":"2026-06-24T00:14:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZJ7VYY7J","created_at":"2026-06-24T00:14:27Z"}],"graph_snapshots":[{"event_id":"sha256:4b9a711bc4cfc7837b24ebdf28e4f13ddee72d4ce2201186d7f3f6ba4e67c082","target":"graph","created_at":"2026-06-24T00:14:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.23825/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Efficient small object detection is bottlenecked by the inherent feature scarcity of tiny targets, which is further aggravated by operations of spatial-domain detectors that indiscriminately discard critical high-frequency details. Recovering these fragile cues within the spatial domain is notoriously difficult, as it often requires computationally expensive architectural upscaling that inadvertently amplifies background noise. To bridge this gap, we propose a paradigm \\textbf{shift from spatial to spectral} feature processing, introducing a holistic solution with the following novelty: (1) A ","authors_text":"Athena Zhuoming Zhong, Dongsheng Hou, Mingxi Yu, Qi Hao, Shihan Qiao, Yanqiao Chen, Yibin Lou, Yuhan Rui, Yutong Wan, Zhen Cao","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T18:09:49Z","title":"From Spatial to Spectral: An Efficient, Frequency-Guided Feature Representation Learner for Small Object Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23825","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1c042ce71014b19f3de469e2ef20979c1a8e592122d4e64840b4639271033a2c","target":"record","created_at":"2026-06-24T00:14:27Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"04fb3d90c250b5ae0f8e72104fe21c9682098c45cdf6ea758bf5809a42de723b","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-22T18:09:49Z","title_canon_sha256":"1acca5fbfbcb4726d85ad8a92e1178d912211236a0f6d223b380b63266652b3c"},"schema_version":"1.0","source":{"id":"2606.23825","kind":"arxiv","version":1}},"canonical_sha256":"ca7f5c63e9258153348959249bcd6e47d16d935783f11c3f76311430118c0a83","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca7f5c63e9258153348959249bcd6e47d16d935783f11c3f76311430118c0a83","first_computed_at":"2026-06-24T00:14:27.971991Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T00:14:27.971991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"glfp1LEdq3XwbeR7ssQlXHonWyGYQDg0aEFI1a69yChSSjo5gFMtfWs00l367IiG48g0tCoVhEzBf9L5lldfAg==","signature_status":"signed_v1","signed_at":"2026-06-24T00:14:27.972393Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23825","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c042ce71014b19f3de469e2ef20979c1a8e592122d4e64840b4639271033a2c","sha256:4b9a711bc4cfc7837b24ebdf28e4f13ddee72d4ce2201186d7f3f6ba4e67c082"],"state_sha256":"1ea5c9d62f8c4946838d34752a256527246f0bcd5335ce8308b9512a4e9c9f59"}