{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:CBVNIR747B564UTIDR2EJUFLD7","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":"0b945203aa4c15abd9cb1e768fc3667e79055a0521549d291ab728e942fd02ca","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-31T09:12:26Z","title_canon_sha256":"c0b33e26df5495906ffeb8f971f0db86faf89f256630d310ebe1ba087171439f"},"schema_version":"1.0","source":{"id":"2108.13697","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.13697","created_at":"2026-07-05T03:10:16Z"},{"alias_kind":"arxiv_version","alias_value":"2108.13697v1","created_at":"2026-07-05T03:10:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.13697","created_at":"2026-07-05T03:10:16Z"},{"alias_kind":"pith_short_12","alias_value":"CBVNIR747B56","created_at":"2026-07-05T03:10:16Z"},{"alias_kind":"pith_short_16","alias_value":"CBVNIR747B564UTI","created_at":"2026-07-05T03:10:16Z"},{"alias_kind":"pith_short_8","alias_value":"CBVNIR74","created_at":"2026-07-05T03:10:16Z"}],"graph_snapshots":[{"event_id":"sha256:96a71aad22ed46cdafd1d1a801610c812be01c1c498a737614a2ff2135f63b5d","target":"graph","created_at":"2026-07-05T03:10:16Z","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/2108.13697/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes a novel Attention-based Multi-Reference Super-resolution network (AMRSR) that, given a low-resolution image, learns to adaptively transfer the most similar texture from multiple reference images to the super-resolution output whilst maintaining spatial coherence. The use of multiple reference images together with attention-based sampling is demonstrated to achieve significantly improved performance over state-of-the-art reference super-resolution approaches on multiple benchmark datasets. Reference super-resolution approaches have recently been proposed to overcome the ill-","authors_text":"Adrian Hilton, Marco Pesavento, Marco Volino","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-31T09:12:26Z","title":"Attention-based Multi-Reference Learning for Image Super-Resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.13697","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:efde4f2cf8641c084f690ccb6c653bebf1f19bde2e2fbc9b01dee709ccf3410e","target":"record","created_at":"2026-07-05T03:10:16Z","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":"0b945203aa4c15abd9cb1e768fc3667e79055a0521549d291ab728e942fd02ca","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-08-31T09:12:26Z","title_canon_sha256":"c0b33e26df5495906ffeb8f971f0db86faf89f256630d310ebe1ba087171439f"},"schema_version":"1.0","source":{"id":"2108.13697","kind":"arxiv","version":1}},"canonical_sha256":"106ad447fcf87bee52681c7444d0ab1ffd2c81b5caa8962173bce3027df251f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"106ad447fcf87bee52681c7444d0ab1ffd2c81b5caa8962173bce3027df251f6","first_computed_at":"2026-07-05T03:10:16.958196Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:10:16.958196Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nj7BRMeybtrq3x/gowahNeymn0leJmJILi0cby1ibttBxNT/cPkzrq+dymP9mrDQ55TziazjkLl/KS8WcrF4DA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:10:16.958599Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.13697","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efde4f2cf8641c084f690ccb6c653bebf1f19bde2e2fbc9b01dee709ccf3410e","sha256:96a71aad22ed46cdafd1d1a801610c812be01c1c498a737614a2ff2135f63b5d"],"state_sha256":"8f06d1a093b9c27d9e8872ada049eb9cbd22a0463723587fa03f6658fa6765de"}