{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XOCT376N2VGLWMBGZAIZTAUQNP","short_pith_number":"pith:XOCT376N","canonical_record":{"source":{"id":"2511.10260","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:49:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fedb0ce7b0596b4153b1ed3da34ef4194ea9720079b90d2d6ee61a93b6994c2b","abstract_canon_sha256":"f6f25f18d564ddc5029ddac54745a4177c635550cd1c7046362ce42d42faf914"},"schema_version":"1.0"},"canonical_sha256":"bb853dffcdd54cbb3026c8119982906bd606c4e57aadcce9f062fd2978d44fe4","source":{"kind":"arxiv","id":"2511.10260","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.10260","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"arxiv_version","alias_value":"2511.10260v2","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.10260","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_12","alias_value":"XOCT376N2VGL","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_16","alias_value":"XOCT376N2VGLWMBG","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_8","alias_value":"XOCT376N","created_at":"2026-07-13T01:17:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XOCT376N2VGLWMBGZAIZTAUQNP","target":"record","payload":{"canonical_record":{"source":{"id":"2511.10260","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:49:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fedb0ce7b0596b4153b1ed3da34ef4194ea9720079b90d2d6ee61a93b6994c2b","abstract_canon_sha256":"f6f25f18d564ddc5029ddac54745a4177c635550cd1c7046362ce42d42faf914"},"schema_version":"1.0"},"canonical_sha256":"bb853dffcdd54cbb3026c8119982906bd606c4e57aadcce9f062fd2978d44fe4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-13T01:17:50.480780Z","signature_b64":"kZ4opfee0CKjsFcEq6WaBQerFxWIGbTQRZZ+BzU6BgH0DDr4GULTuy1RZ8lU7iWxpAHqksDt6nM4hkyKnJqBBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bb853dffcdd54cbb3026c8119982906bd606c4e57aadcce9f062fd2978d44fe4","last_reissued_at":"2026-07-13T01:17:50.479739Z","signature_status":"signed_v1","first_computed_at":"2026-07-13T01:17:50.479739Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2511.10260","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-13T01:17:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"37fi8TTYiM+sdQIW71Kt5T5eMUzcrZawOeLqL8zxS8tz8EGN4gjdTdkXu620BvxShHtoERJXVIpd0nCysftwCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:04:55.294873Z"},"content_sha256":"2c7eed5633f2ad0320687a3cdf11c263cae75b306736271ed86188cb8c767344","schema_version":"1.0","event_id":"sha256:2c7eed5633f2ad0320687a3cdf11c263cae75b306736271ed86188cb8c767344"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XOCT376N2VGLWMBGZAIZTAUQNP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"H3Former: Hypergraph-based Semantic-Aware Aggregation via Hyperbolic Hierarchical Contrastive Loss for Fine-Grained Visual Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Kuiyang Huang, Siqi Li, Yongji Zhang, Yue Gao, Yu Jiang","submitted_at":"2025-11-13T12:49:10Z","abstract_excerpt":"Fine-Grained Visual Classification (FGVC) remains a challenging task due to subtle inter-class differences and large intra-class variations. Existing approaches typically rely on feature-selection mechanisms or region-proposal strategies to localize discriminative regions for semantic analysis. However, these methods often fail to capture discriminative cues comprehensively while introducing substantial category-agnostic redundancy. To address these limitations, we propose H3Former, a novel token-to-region framework that leverages high-order semantic relations to aggregate local fine-grained r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.10260","kind":"arxiv","version":2},"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/2511.10260/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-13T01:17:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"foyOzb8nYnnoGXl4sZRiIB9LnuG+wSgVH3/0OjXpHK2ZCXHt6I3HDpXNFqTc0V28eZ7sY81zwzB+b0lOnneWCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:04:55.295962Z"},"content_sha256":"86233960b94a47963b31344e218f499caccc03e55ef62d0fa3ae70097a8559f3","schema_version":"1.0","event_id":"sha256:86233960b94a47963b31344e218f499caccc03e55ef62d0fa3ae70097a8559f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XOCT376N2VGLWMBGZAIZTAUQNP/bundle.json","state_url":"https://pith.science/pith/XOCT376N2VGLWMBGZAIZTAUQNP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XOCT376N2VGLWMBGZAIZTAUQNP/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T21:04:55Z","links":{"resolver":"https://pith.science/pith/XOCT376N2VGLWMBGZAIZTAUQNP","bundle":"https://pith.science/pith/XOCT376N2VGLWMBGZAIZTAUQNP/bundle.json","state":"https://pith.science/pith/XOCT376N2VGLWMBGZAIZTAUQNP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XOCT376N2VGLWMBGZAIZTAUQNP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XOCT376N2VGLWMBGZAIZTAUQNP","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":"f6f25f18d564ddc5029ddac54745a4177c635550cd1c7046362ce42d42faf914","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:49:10Z","title_canon_sha256":"fedb0ce7b0596b4153b1ed3da34ef4194ea9720079b90d2d6ee61a93b6994c2b"},"schema_version":"1.0","source":{"id":"2511.10260","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.10260","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"arxiv_version","alias_value":"2511.10260v2","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.10260","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_12","alias_value":"XOCT376N2VGL","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_16","alias_value":"XOCT376N2VGLWMBG","created_at":"2026-07-13T01:17:50Z"},{"alias_kind":"pith_short_8","alias_value":"XOCT376N","created_at":"2026-07-13T01:17:50Z"}],"graph_snapshots":[{"event_id":"sha256:86233960b94a47963b31344e218f499caccc03e55ef62d0fa3ae70097a8559f3","target":"graph","created_at":"2026-07-13T01:17:50Z","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/2511.10260/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-Grained Visual Classification (FGVC) remains a challenging task due to subtle inter-class differences and large intra-class variations. Existing approaches typically rely on feature-selection mechanisms or region-proposal strategies to localize discriminative regions for semantic analysis. However, these methods often fail to capture discriminative cues comprehensively while introducing substantial category-agnostic redundancy. To address these limitations, we propose H3Former, a novel token-to-region framework that leverages high-order semantic relations to aggregate local fine-grained r","authors_text":"Kuiyang Huang, Siqi Li, Yongji Zhang, Yue Gao, Yu Jiang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:49:10Z","title":"H3Former: Hypergraph-based Semantic-Aware Aggregation via Hyperbolic Hierarchical Contrastive Loss for Fine-Grained Visual Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.10260","kind":"arxiv","version":2},"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":"sha256:2c7eed5633f2ad0320687a3cdf11c263cae75b306736271ed86188cb8c767344","target":"record","created_at":"2026-07-13T01:17:50Z","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":"f6f25f18d564ddc5029ddac54745a4177c635550cd1c7046362ce42d42faf914","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:49:10Z","title_canon_sha256":"fedb0ce7b0596b4153b1ed3da34ef4194ea9720079b90d2d6ee61a93b6994c2b"},"schema_version":"1.0","source":{"id":"2511.10260","kind":"arxiv","version":2}},"canonical_sha256":"bb853dffcdd54cbb3026c8119982906bd606c4e57aadcce9f062fd2978d44fe4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bb853dffcdd54cbb3026c8119982906bd606c4e57aadcce9f062fd2978d44fe4","first_computed_at":"2026-07-13T01:17:50.479739Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-13T01:17:50.479739Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kZ4opfee0CKjsFcEq6WaBQerFxWIGbTQRZZ+BzU6BgH0DDr4GULTuy1RZ8lU7iWxpAHqksDt6nM4hkyKnJqBBw==","signature_status":"signed_v1","signed_at":"2026-07-13T01:17:50.480780Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.10260","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c7eed5633f2ad0320687a3cdf11c263cae75b306736271ed86188cb8c767344","sha256:86233960b94a47963b31344e218f499caccc03e55ef62d0fa3ae70097a8559f3"],"state_sha256":"ede3fee00f0dad113445e63856a48a4769f916f8a4110a69a732eeb53bdc0329"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"65Bvv5EGPg/qp1ytXwnTPYj7vrv2YSyBQLCaE8FJNg3m9q/UWT8aDQznj6wuyqpoKc5bOmD6tbE+tgZQjJenAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T21:04:55.301875Z","bundle_sha256":"b28cb871e868547cad6a6489208ed187927bc74024481e98c11f10926600722b"}}