{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XUFL4QCSO3X7A46KN2YSY6VVJL","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":"cea73b28ba751c118de6d2ec9dbf02781e714fffde8591bec1fdeb42ff1283b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T09:02:48Z","title_canon_sha256":"b52f1167c4da50972d2580b7cc06f4592e7af0e3e02b95d2eb49074f9a737f27"},"schema_version":"1.0","source":{"id":"2606.27862","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.27862","created_at":"2026-06-29T01:14:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.27862v1","created_at":"2026-06-29T01:14:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.27862","created_at":"2026-06-29T01:14:50Z"},{"alias_kind":"pith_short_12","alias_value":"XUFL4QCSO3X7","created_at":"2026-06-29T01:14:50Z"},{"alias_kind":"pith_short_16","alias_value":"XUFL4QCSO3X7A46K","created_at":"2026-06-29T01:14:50Z"},{"alias_kind":"pith_short_8","alias_value":"XUFL4QCS","created_at":"2026-06-29T01:14:50Z"}],"graph_snapshots":[{"event_id":"sha256:551b8340467f4a288cdfb199c92c29c91abe699b28b95f4c69b546cfcbe52a5f","target":"graph","created_at":"2026-06-29T01:14:50Z","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/2606.27862/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Implicit Neural Representations (INRs) parameterized by multilayer perceptrons excel at modeling continuous signals. However, a key challenge persists as INRs fundamentally suffer from spectral bias and information cross-talk. When a single network attempts to capture multi-scale phenomena, high-frequency weight updates destructively interfere with the underlying low-frequency structural approximation. We introduce Scale and Learn INR (ScaLe-INR), a novel multi-branch architecture that resolves these limitations by explicitly matching the signal's frequency spectrum with the optimal operating ","authors_text":"Athulya Ratnayake, Avishka Ranasinghe, Buwaneka Epakanda, Mario De Silva, Pandula Thennakoon, Parakrama Ekanayake, Roshan Godaliyadda","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T09:02:48Z","title":"ScaLe-INR: Scale and Learn Implicit Neural Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.27862","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":"sha256:25fb9c0226a74d2e3aa3b1f9afc3cf389b2d571832918bd1a353f8742b20f71f","target":"record","created_at":"2026-06-29T01:14:50Z","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":"cea73b28ba751c118de6d2ec9dbf02781e714fffde8591bec1fdeb42ff1283b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-26T09:02:48Z","title_canon_sha256":"b52f1167c4da50972d2580b7cc06f4592e7af0e3e02b95d2eb49074f9a737f27"},"schema_version":"1.0","source":{"id":"2606.27862","kind":"arxiv","version":1}},"canonical_sha256":"bd0abe405276eff073ca6eb12c7ab54ad85f719b060846625fe8ec23a3a8c1b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd0abe405276eff073ca6eb12c7ab54ad85f719b060846625fe8ec23a3a8c1b0","first_computed_at":"2026-06-29T01:14:50.993624Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-29T01:14:50.993624Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mn1ObMDkYhvzrogxjtbxfOfZ1kVzjZU0Hb2R2BfEFXk5azZO2osQPaQqdefAS0n6PfKiVS2ZfTjwi/Us/f2xCw==","signature_status":"signed_v1","signed_at":"2026-06-29T01:14:50.994031Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.27862","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25fb9c0226a74d2e3aa3b1f9afc3cf389b2d571832918bd1a353f8742b20f71f","sha256:551b8340467f4a288cdfb199c92c29c91abe699b28b95f4c69b546cfcbe52a5f"],"state_sha256":"7e01d79b85df0bbb2ce7f65be537dd94fadcf868a31d09a29055b9e9963d0fa8"}