{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:GMYPNPNT6PCGFLLARU33P5ZMCM","short_pith_number":"pith:GMYPNPNT","canonical_record":{"source":{"id":"2002.10191","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T12:17:56Z","cross_cats_sorted":[],"title_canon_sha256":"ff40059c98add9620862046a6b6d06d824df411aa3d6fab706d71f42037f756e","abstract_canon_sha256":"35ae068a75e99d159c7d5f4478c07de1cf7218230c374c1ff05a2ff651fb0474"},"schema_version":"1.0"},"canonical_sha256":"3330f6bdb3f3c462ad608d37b7f72c1332afb36202dec43ee6fa7b84700905fe","source":{"kind":"arxiv","id":"2002.10191","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10191","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10191v1","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10191","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_12","alias_value":"GMYPNPNT6PCG","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_16","alias_value":"GMYPNPNT6PCGFLLA","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_8","alias_value":"GMYPNPNT","created_at":"2026-07-05T00:43:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:GMYPNPNT6PCGFLLARU33P5ZMCM","target":"record","payload":{"canonical_record":{"source":{"id":"2002.10191","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T12:17:56Z","cross_cats_sorted":[],"title_canon_sha256":"ff40059c98add9620862046a6b6d06d824df411aa3d6fab706d71f42037f756e","abstract_canon_sha256":"35ae068a75e99d159c7d5f4478c07de1cf7218230c374c1ff05a2ff651fb0474"},"schema_version":"1.0"},"canonical_sha256":"3330f6bdb3f3c462ad608d37b7f72c1332afb36202dec43ee6fa7b84700905fe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:43:15.384505Z","signature_b64":"M9opLIiouFWH+sZHsbH1baBK+pmzGgeR/XDdPjNI8b9C+KgRUqVOyRx0bFHRvNmWeCz9jN2GRI0uROdQs8tqBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3330f6bdb3f3c462ad608d37b7f72c1332afb36202dec43ee6fa7b84700905fe","last_reissued_at":"2026-07-05T00:43:15.384000Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:43:15.384000Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.10191","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:43:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6nGgUOUxPpYjKj/Kei/fi7QBCqPo62ifg0y28bl/DQXmk9a/ntCx14IEsPMWU/urGsB7zPik5Vr3J66XrkIZDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:57:09.046589Z"},"content_sha256":"faa33fe43e2a8b0541cdfcd94c09e567bd25bb173c870e1493acf7741d5b2a11","schema_version":"1.0","event_id":"sha256:faa33fe43e2a8b0541cdfcd94c09e567bd25bb173c870e1493acf7741d5b2a11"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:GMYPNPNT6PCGFLLARU33P5ZMCM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Attentive Pairwise Interaction for Fine-Grained Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Peiqin Zhuang, Yali Wang, Yu Qiao","submitted_at":"2020-02-24T12:17:56Z","abstract_excerpt":"Fine-grained classification is a challenging problem, due to subtle differences among highly-confused categories. Most approaches address this difficulty by learning discriminative representation of individual input image. On the other hand, humans can effectively identify contrastive clues by comparing image pairs. Inspired by this fact, this paper proposes a simple but effective Attentive Pairwise Interaction Network (API-Net), which can progressively recognize a pair of fine-grained images by interaction. Specifically, API-Net first learns a mutual feature vector to capture semantic differe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10191","kind":"arxiv","version":1},"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/2002.10191/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":"2026-07-05T00:43:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rx6m/N1ShBJCT0td0Fd3Gbr2OLFERzU9D0V1LUQW38SIi8O3epUs/5wEP+HESu8wF7MHvel+fRkqCOsR5eaUDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:57:09.047427Z"},"content_sha256":"97ec0767d6f9ac9ecc3e2979f618f7d874081988979f08f1ae205c34c59c4a1b","schema_version":"1.0","event_id":"sha256:97ec0767d6f9ac9ecc3e2979f618f7d874081988979f08f1ae205c34c59c4a1b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/bundle.json","state_url":"https://pith.science/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/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":"2026-08-04T03:57:09Z","links":{"resolver":"https://pith.science/pith/GMYPNPNT6PCGFLLARU33P5ZMCM","bundle":"https://pith.science/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/bundle.json","state":"https://pith.science/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GMYPNPNT6PCGFLLARU33P5ZMCM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:GMYPNPNT6PCGFLLARU33P5ZMCM","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":"35ae068a75e99d159c7d5f4478c07de1cf7218230c374c1ff05a2ff651fb0474","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T12:17:56Z","title_canon_sha256":"ff40059c98add9620862046a6b6d06d824df411aa3d6fab706d71f42037f756e"},"schema_version":"1.0","source":{"id":"2002.10191","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10191","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10191v1","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10191","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_12","alias_value":"GMYPNPNT6PCG","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_16","alias_value":"GMYPNPNT6PCGFLLA","created_at":"2026-07-05T00:43:15Z"},{"alias_kind":"pith_short_8","alias_value":"GMYPNPNT","created_at":"2026-07-05T00:43:15Z"}],"graph_snapshots":[{"event_id":"sha256:97ec0767d6f9ac9ecc3e2979f618f7d874081988979f08f1ae205c34c59c4a1b","target":"graph","created_at":"2026-07-05T00:43:15Z","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/2002.10191/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-grained classification is a challenging problem, due to subtle differences among highly-confused categories. Most approaches address this difficulty by learning discriminative representation of individual input image. On the other hand, humans can effectively identify contrastive clues by comparing image pairs. Inspired by this fact, this paper proposes a simple but effective Attentive Pairwise Interaction Network (API-Net), which can progressively recognize a pair of fine-grained images by interaction. Specifically, API-Net first learns a mutual feature vector to capture semantic differe","authors_text":"Peiqin Zhuang, Yali Wang, Yu Qiao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T12:17:56Z","title":"Learning Attentive Pairwise Interaction for Fine-Grained Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10191","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:faa33fe43e2a8b0541cdfcd94c09e567bd25bb173c870e1493acf7741d5b2a11","target":"record","created_at":"2026-07-05T00:43:15Z","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":"35ae068a75e99d159c7d5f4478c07de1cf7218230c374c1ff05a2ff651fb0474","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-24T12:17:56Z","title_canon_sha256":"ff40059c98add9620862046a6b6d06d824df411aa3d6fab706d71f42037f756e"},"schema_version":"1.0","source":{"id":"2002.10191","kind":"arxiv","version":1}},"canonical_sha256":"3330f6bdb3f3c462ad608d37b7f72c1332afb36202dec43ee6fa7b84700905fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3330f6bdb3f3c462ad608d37b7f72c1332afb36202dec43ee6fa7b84700905fe","first_computed_at":"2026-07-05T00:43:15.384000Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:43:15.384000Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M9opLIiouFWH+sZHsbH1baBK+pmzGgeR/XDdPjNI8b9C+KgRUqVOyRx0bFHRvNmWeCz9jN2GRI0uROdQs8tqBw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:43:15.384505Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.10191","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:faa33fe43e2a8b0541cdfcd94c09e567bd25bb173c870e1493acf7741d5b2a11","sha256:97ec0767d6f9ac9ecc3e2979f618f7d874081988979f08f1ae205c34c59c4a1b"],"state_sha256":"6b4a99aa6bf8f2d4e33c7ad8b1a0b8bae9fbfa0488de63099434a58bc4dcf3d6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xhs6PfaQTP3kU9uujV/i353CAUVPuCawWvfLoweWpg8uDv88Fn/A/kTxWGaXHiI5vDEe8IRTNQMeGoaG2lfAAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T03:57:09.054190Z","bundle_sha256":"cbc64f3ef0b7198ae0e12e21ef97d008e26613946f03372786bb798f6f66baf2"}}