{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GXFLDY5B6JVIFUVRKDL65RI7W3","short_pith_number":"pith:GXFLDY5B","canonical_record":{"source":{"id":"2408.14192","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-26T11:36:38Z","cross_cats_sorted":[],"title_canon_sha256":"aab4dba405ecafeed835b411d03dd84cddadbefb7df0063c1f5344b7664a0661","abstract_canon_sha256":"12866a32203f7dfafb75941f2d7fdca63481f851c19e4cd7ade039322eec8f2b"},"schema_version":"1.0"},"canonical_sha256":"35cab1e3a1f26a82d2b150d7eec51fb6d708ddfa628f74d33cdd8d3bee67781a","source":{"kind":"arxiv","id":"2408.14192","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.14192","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"arxiv_version","alias_value":"2408.14192v1","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.14192","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_12","alias_value":"GXFLDY5B6JVI","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_16","alias_value":"GXFLDY5B6JVIFUVR","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_8","alias_value":"GXFLDY5B","created_at":"2026-07-05T08:59:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GXFLDY5B6JVIFUVRKDL65RI7W3","target":"record","payload":{"canonical_record":{"source":{"id":"2408.14192","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-26T11:36:38Z","cross_cats_sorted":[],"title_canon_sha256":"aab4dba405ecafeed835b411d03dd84cddadbefb7df0063c1f5344b7664a0661","abstract_canon_sha256":"12866a32203f7dfafb75941f2d7fdca63481f851c19e4cd7ade039322eec8f2b"},"schema_version":"1.0"},"canonical_sha256":"35cab1e3a1f26a82d2b150d7eec51fb6d708ddfa628f74d33cdd8d3bee67781a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:59:17.578508Z","signature_b64":"kn3NK4M4JDTzbhwRzvXSLhW28xdBtw4rodCtQFcH5xHiCHQmPaU0299vJsgzarnVjLrw04lIw4RwI6791iihDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"35cab1e3a1f26a82d2b150d7eec51fb6d708ddfa628f74d33cdd8d3bee67781a","last_reissued_at":"2026-07-05T08:59:17.578035Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:59:17.578035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.14192","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":"2026-07-05T08:59:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h4aOg5hqwhIEAuCvU+WKhFsNmDR/kL/VhKOJ1fcmm3gcJwikiThfQdOd2qusMTdet8Ylc9e7vLb5O0EQl5yJDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:56:55.660202Z"},"content_sha256":"89ff3eb4821b0b099b1f4d25e9ad16fde4c5853a743f02ad0bb8b5b087e95f4c","schema_version":"1.0","event_id":"sha256:89ff3eb4821b0b099b1f4d25e9ad16fde4c5853a743f02ad0bb8b5b087e95f4c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GXFLDY5B6JVIFUVRKDL65RI7W3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Feature Aligning Few shot Learning Method Using Local Descriptors Weighted Rules","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingchen Yan","submitted_at":"2024-08-26T11:36:38Z","abstract_excerpt":"Few-shot classification involves identifying new categories using a limited number of labeled samples. Current few-shot classification methods based on local descriptors primarily leverage underlying consistent features across visible and invisible classes, facing challenges including redundant neighboring information, noisy representations, and limited interpretability. This paper proposes a Feature Aligning Few-shot Learning Method Using Local Descriptors Weighted Rules (FAFD-LDWR). It innovatively introduces a cross-normalization method into few-shot image classification to preserve the dis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.14192","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/2408.14192/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":"2026-07-05T08:59:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/8yWv0fXba3FYfZWMekRIdNuee5fV+8H359nZWMOlOQFdG4laydtFGaCrnoP6ssBis2sfgbTWcSAdMCKDk7cAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:56:55.661110Z"},"content_sha256":"3684059952d83046a8f78bb519c41b0f3e7cf4ed7de029bc1ab35d301f9f658a","schema_version":"1.0","event_id":"sha256:3684059952d83046a8f78bb519c41b0f3e7cf4ed7de029bc1ab35d301f9f658a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/bundle.json","state_url":"https://pith.science/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/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":"2026-08-05T15:56:55Z","links":{"resolver":"https://pith.science/pith/GXFLDY5B6JVIFUVRKDL65RI7W3","bundle":"https://pith.science/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/bundle.json","state":"https://pith.science/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GXFLDY5B6JVIFUVRKDL65RI7W3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GXFLDY5B6JVIFUVRKDL65RI7W3","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":"12866a32203f7dfafb75941f2d7fdca63481f851c19e4cd7ade039322eec8f2b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-26T11:36:38Z","title_canon_sha256":"aab4dba405ecafeed835b411d03dd84cddadbefb7df0063c1f5344b7664a0661"},"schema_version":"1.0","source":{"id":"2408.14192","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.14192","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"arxiv_version","alias_value":"2408.14192v1","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.14192","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_12","alias_value":"GXFLDY5B6JVI","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_16","alias_value":"GXFLDY5B6JVIFUVR","created_at":"2026-07-05T08:59:17Z"},{"alias_kind":"pith_short_8","alias_value":"GXFLDY5B","created_at":"2026-07-05T08:59:17Z"}],"graph_snapshots":[{"event_id":"sha256:3684059952d83046a8f78bb519c41b0f3e7cf4ed7de029bc1ab35d301f9f658a","target":"graph","created_at":"2026-07-05T08:59:17Z","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/2408.14192/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-shot classification involves identifying new categories using a limited number of labeled samples. Current few-shot classification methods based on local descriptors primarily leverage underlying consistent features across visible and invisible classes, facing challenges including redundant neighboring information, noisy representations, and limited interpretability. This paper proposes a Feature Aligning Few-shot Learning Method Using Local Descriptors Weighted Rules (FAFD-LDWR). It innovatively introduces a cross-normalization method into few-shot image classification to preserve the dis","authors_text":"Bingchen Yan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-26T11:36:38Z","title":"Feature Aligning Few shot Learning Method Using Local Descriptors Weighted Rules"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.14192","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":"sha256:89ff3eb4821b0b099b1f4d25e9ad16fde4c5853a743f02ad0bb8b5b087e95f4c","target":"record","created_at":"2026-07-05T08:59:17Z","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":"12866a32203f7dfafb75941f2d7fdca63481f851c19e4cd7ade039322eec8f2b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-26T11:36:38Z","title_canon_sha256":"aab4dba405ecafeed835b411d03dd84cddadbefb7df0063c1f5344b7664a0661"},"schema_version":"1.0","source":{"id":"2408.14192","kind":"arxiv","version":1}},"canonical_sha256":"35cab1e3a1f26a82d2b150d7eec51fb6d708ddfa628f74d33cdd8d3bee67781a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"35cab1e3a1f26a82d2b150d7eec51fb6d708ddfa628f74d33cdd8d3bee67781a","first_computed_at":"2026-07-05T08:59:17.578035Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:59:17.578035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kn3NK4M4JDTzbhwRzvXSLhW28xdBtw4rodCtQFcH5xHiCHQmPaU0299vJsgzarnVjLrw04lIw4RwI6791iihDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:59:17.578508Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.14192","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:89ff3eb4821b0b099b1f4d25e9ad16fde4c5853a743f02ad0bb8b5b087e95f4c","sha256:3684059952d83046a8f78bb519c41b0f3e7cf4ed7de029bc1ab35d301f9f658a"],"state_sha256":"eaed6b13af0dc053148d214d15d576880624dde78998f2daff47153ded14f8e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E2jhQ59fXkZlP6dJLLYrO7hHCIUXrbou4TIWmZ7IM8q6XexgjfS/dEzZVleRmpSLAkJZ8aym50oAAMQRMJC7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:56:55.667866Z","bundle_sha256":"224c483ef50b0090e661fb1e003147573f71e18913e00be54cca2ca9c231dd46"}}