{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:37KYW4HHNF5SELFAWSPQIYB2SD","short_pith_number":"pith:37KYW4HH","canonical_record":{"source":{"id":"2208.00617","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-01T05:36:27Z","cross_cats_sorted":[],"title_canon_sha256":"c6ef93cd8648b34baea4104ec1e91f2659f3144b43751e733e7e7f0a3144161c","abstract_canon_sha256":"37fe3fa98bff7afa6c8ec18141ee655b42c79da63bf99067a855bf6c3317c678"},"schema_version":"1.0"},"canonical_sha256":"dfd58b70e7697b222ca0b49f04603a90fc82e038996a4f645e7f1f16646862a9","source":{"kind":"arxiv","id":"2208.00617","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.00617","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"arxiv_version","alias_value":"2208.00617v1","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.00617","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_12","alias_value":"37KYW4HHNF5S","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_16","alias_value":"37KYW4HHNF5SELFA","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_8","alias_value":"37KYW4HH","created_at":"2026-07-05T04:45:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:37KYW4HHNF5SELFAWSPQIYB2SD","target":"record","payload":{"canonical_record":{"source":{"id":"2208.00617","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-01T05:36:27Z","cross_cats_sorted":[],"title_canon_sha256":"c6ef93cd8648b34baea4104ec1e91f2659f3144b43751e733e7e7f0a3144161c","abstract_canon_sha256":"37fe3fa98bff7afa6c8ec18141ee655b42c79da63bf99067a855bf6c3317c678"},"schema_version":"1.0"},"canonical_sha256":"dfd58b70e7697b222ca0b49f04603a90fc82e038996a4f645e7f1f16646862a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:45:02.866377Z","signature_b64":"pFGFBn5owFdRNMHmEpEi8Awy0PcPnYdIzUrzKmqowQJHzoUsFvL2u4U0GYwucFzGaqDCVt6MAtYelmvp753jCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dfd58b70e7697b222ca0b49f04603a90fc82e038996a4f645e7f1f16646862a9","last_reissued_at":"2026-07-05T04:45:02.865875Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:45:02.865875Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.00617","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":"2026-07-05T04:45:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cVKwskbMdAZ5toJpuiYkJSDYoIDVrpUAZnQ1c2d7aMRaNbpYJomVXRV9QxrdNIdswkyyzNQpEuIwDp+7CT4CAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T11:28:31.569361Z"},"content_sha256":"227f26245482b637ea906a939d2502d3fd1cecfa4bde251cef9db0e43021a02a","schema_version":"1.0","event_id":"sha256:227f26245482b637ea906a939d2502d3fd1cecfa4bde251cef9db0e43021a02a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:37KYW4HHNF5SELFAWSPQIYB2SD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baosheng Yu, Haiming Xu, Lingqiao Liu, Yangyang Shu","submitted_at":"2022-08-01T05:36:27Z","abstract_excerpt":"The challenge of fine-grained visual recognition often lies in discovering the key discriminative regions. While such regions can be automatically identified from a large-scale labeled dataset, a similar method might become less effective when only a few annotations are available. In low data regimes, a network often struggles to choose the correct regions for recognition and tends to overfit spurious correlated patterns from the training data. To tackle this issue, this paper proposes the self-boosting attention mechanism, a novel method for regularizing the network to focus on the key region"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.00617","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/2208.00617/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":"2026-07-05T04:45:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pv+2aHCIfTTXaNvccWRfTtWT4GGI8Dok+mqUe10J/V1KM9C7Cg1tXX0Xq5J/GmsfzkDyf2WJBUDE0NkllFJ0Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T11:28:31.569853Z"},"content_sha256":"0afd38e811dbb7b58a43d35ba6fa2c2a72b7f117dc13538f06f8dbfbfdbe3ad9","schema_version":"1.0","event_id":"sha256:0afd38e811dbb7b58a43d35ba6fa2c2a72b7f117dc13538f06f8dbfbfdbe3ad9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/37KYW4HHNF5SELFAWSPQIYB2SD/bundle.json","state_url":"https://pith.science/pith/37KYW4HHNF5SELFAWSPQIYB2SD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/37KYW4HHNF5SELFAWSPQIYB2SD/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":"2026-08-06T11:28:31Z","links":{"resolver":"https://pith.science/pith/37KYW4HHNF5SELFAWSPQIYB2SD","bundle":"https://pith.science/pith/37KYW4HHNF5SELFAWSPQIYB2SD/bundle.json","state":"https://pith.science/pith/37KYW4HHNF5SELFAWSPQIYB2SD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/37KYW4HHNF5SELFAWSPQIYB2SD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:37KYW4HHNF5SELFAWSPQIYB2SD","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":"37fe3fa98bff7afa6c8ec18141ee655b42c79da63bf99067a855bf6c3317c678","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-01T05:36:27Z","title_canon_sha256":"c6ef93cd8648b34baea4104ec1e91f2659f3144b43751e733e7e7f0a3144161c"},"schema_version":"1.0","source":{"id":"2208.00617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.00617","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"arxiv_version","alias_value":"2208.00617v1","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.00617","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_12","alias_value":"37KYW4HHNF5S","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_16","alias_value":"37KYW4HHNF5SELFA","created_at":"2026-07-05T04:45:02Z"},{"alias_kind":"pith_short_8","alias_value":"37KYW4HH","created_at":"2026-07-05T04:45:02Z"}],"graph_snapshots":[{"event_id":"sha256:0afd38e811dbb7b58a43d35ba6fa2c2a72b7f117dc13538f06f8dbfbfdbe3ad9","target":"graph","created_at":"2026-07-05T04:45:02Z","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/2208.00617/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The challenge of fine-grained visual recognition often lies in discovering the key discriminative regions. While such regions can be automatically identified from a large-scale labeled dataset, a similar method might become less effective when only a few annotations are available. In low data regimes, a network often struggles to choose the correct regions for recognition and tends to overfit spurious correlated patterns from the training data. To tackle this issue, this paper proposes the self-boosting attention mechanism, a novel method for regularizing the network to focus on the key region","authors_text":"Baosheng Yu, Haiming Xu, Lingqiao Liu, Yangyang Shu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-01T05:36:27Z","title":"Improving Fine-Grained Visual Recognition in Low Data Regimes via Self-Boosting Attention Mechanism"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.00617","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":"sha256:227f26245482b637ea906a939d2502d3fd1cecfa4bde251cef9db0e43021a02a","target":"record","created_at":"2026-07-05T04:45:02Z","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":"37fe3fa98bff7afa6c8ec18141ee655b42c79da63bf99067a855bf6c3317c678","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-01T05:36:27Z","title_canon_sha256":"c6ef93cd8648b34baea4104ec1e91f2659f3144b43751e733e7e7f0a3144161c"},"schema_version":"1.0","source":{"id":"2208.00617","kind":"arxiv","version":1}},"canonical_sha256":"dfd58b70e7697b222ca0b49f04603a90fc82e038996a4f645e7f1f16646862a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dfd58b70e7697b222ca0b49f04603a90fc82e038996a4f645e7f1f16646862a9","first_computed_at":"2026-07-05T04:45:02.865875Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:45:02.865875Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pFGFBn5owFdRNMHmEpEi8Awy0PcPnYdIzUrzKmqowQJHzoUsFvL2u4U0GYwucFzGaqDCVt6MAtYelmvp753jCg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:45:02.866377Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.00617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:227f26245482b637ea906a939d2502d3fd1cecfa4bde251cef9db0e43021a02a","sha256:0afd38e811dbb7b58a43d35ba6fa2c2a72b7f117dc13538f06f8dbfbfdbe3ad9"],"state_sha256":"eb3f451fecc65c980d80a1afb306be5038324f11f7ea6f804b6f56903bab3420"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sC/KBk5KhL/aDodGUfm8Wdefo0lEgNsNvFy9uixlWmueKIo6XVReUNg19aYgmYBI20nCguMnDNccfssAV09zCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T11:28:31.574764Z","bundle_sha256":"74878af1a245206a341ae9aa13b13aa97bfefb7803da232dc252db99f09cd861"}}