{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:LU35REBTXWSAKGT6IZ7WTBONN5","short_pith_number":"pith:LU35REBT","canonical_record":{"source":{"id":"2010.03255","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-07T08:13:42Z","cross_cats_sorted":[],"title_canon_sha256":"b97bc26da7eb1cf00aa8e6be1fe4dcc5d70ea8a322c324ff19a99436d1c4750a","abstract_canon_sha256":"52537e951804da63f55a914d6965e395b3bd94bfc324e9961d22b0bba0f999dc"},"schema_version":"1.0"},"canonical_sha256":"5d37d89033bda4051a7e467f6985cd6f42eaab36b88577ebc6ec8179d39a5803","source":{"kind":"arxiv","id":"2010.03255","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.03255","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"arxiv_version","alias_value":"2010.03255v3","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.03255","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_12","alias_value":"LU35REBTXWSA","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_16","alias_value":"LU35REBTXWSAKGT6","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_8","alias_value":"LU35REBT","created_at":"2026-07-05T03:08:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:LU35REBTXWSAKGT6IZ7WTBONN5","target":"record","payload":{"canonical_record":{"source":{"id":"2010.03255","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-07T08:13:42Z","cross_cats_sorted":[],"title_canon_sha256":"b97bc26da7eb1cf00aa8e6be1fe4dcc5d70ea8a322c324ff19a99436d1c4750a","abstract_canon_sha256":"52537e951804da63f55a914d6965e395b3bd94bfc324e9961d22b0bba0f999dc"},"schema_version":"1.0"},"canonical_sha256":"5d37d89033bda4051a7e467f6985cd6f42eaab36b88577ebc6ec8179d39a5803","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:08:43.009758Z","signature_b64":"unL+U/eVgrl4Y7SwXvbWVi8aTrgpPcD+NYxSzjkCWIja0v9Z0AvEZvqt/JhZkrdQNIb7tYoHkwDr+0aV7N1XAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d37d89033bda4051a7e467f6985cd6f42eaab36b88577ebc6ec8179d39a5803","last_reissued_at":"2026-07-05T03:08:43.009384Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:08:43.009384Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.03255","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:08:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xVa3GbzvjeFurBz2It4nC0elUZGjIDS2EsPiCkiCSTjzSJJyzCVFsjEE999DP0DH3n2+EC91zyDt2G0/alZTDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:28:09.281827Z"},"content_sha256":"f7f8fc628c9f2a6e188b67c873eeb90a560339a601a375c946813d016b464147","schema_version":"1.0","event_id":"sha256:f7f8fc628c9f2a6e188b67c873eeb90a560339a601a375c946813d016b464147"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:LU35REBTXWSAKGT6IZ7WTBONN5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Variational Feature Disentangling for Fine-Grained Few-Shot Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dimitris Samaras, Hieu Le, Jingyi Xu, Mingzhen Huang, ShahRukh Athar","submitted_at":"2020-10-07T08:13:42Z","abstract_excerpt":"Fine-grained few-shot recognition often suffers from the problem of training data scarcity for novel categories.The network tends to overfit and does not generalize well to unseen classes due to insufficient training data. Many methods have been proposed to synthesize additional data to support the training. In this paper, we focus one enlarging the intra-class variance of the unseen class to improve few-shot classification performance. We assume that the distribution of intra-class variance generalizes across the base class and the novel class. Thus, the intra-class variance of the base set c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.03255","kind":"arxiv","version":3},"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/2010.03255/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":"2026-07-05T03:08:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3DhWnLA8B+xryYnYUpc3XMKygzueMf/knVuV8HXJehholGqIT0iK5SblPyoBi2B8ASQTA2UQU2e1MgPBFa9IDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:28:09.282445Z"},"content_sha256":"a1515c329fc1d274ebf185a6f5eae042bce014fb2f62a2529cd5cdef59f7bc4a","schema_version":"1.0","event_id":"sha256:a1515c329fc1d274ebf185a6f5eae042bce014fb2f62a2529cd5cdef59f7bc4a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LU35REBTXWSAKGT6IZ7WTBONN5/bundle.json","state_url":"https://pith.science/pith/LU35REBTXWSAKGT6IZ7WTBONN5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LU35REBTXWSAKGT6IZ7WTBONN5/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":"2026-08-19T11:28:09Z","links":{"resolver":"https://pith.science/pith/LU35REBTXWSAKGT6IZ7WTBONN5","bundle":"https://pith.science/pith/LU35REBTXWSAKGT6IZ7WTBONN5/bundle.json","state":"https://pith.science/pith/LU35REBTXWSAKGT6IZ7WTBONN5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LU35REBTXWSAKGT6IZ7WTBONN5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:LU35REBTXWSAKGT6IZ7WTBONN5","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":"52537e951804da63f55a914d6965e395b3bd94bfc324e9961d22b0bba0f999dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-07T08:13:42Z","title_canon_sha256":"b97bc26da7eb1cf00aa8e6be1fe4dcc5d70ea8a322c324ff19a99436d1c4750a"},"schema_version":"1.0","source":{"id":"2010.03255","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.03255","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"arxiv_version","alias_value":"2010.03255v3","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.03255","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_12","alias_value":"LU35REBTXWSA","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_16","alias_value":"LU35REBTXWSAKGT6","created_at":"2026-07-05T03:08:43Z"},{"alias_kind":"pith_short_8","alias_value":"LU35REBT","created_at":"2026-07-05T03:08:43Z"}],"graph_snapshots":[{"event_id":"sha256:a1515c329fc1d274ebf185a6f5eae042bce014fb2f62a2529cd5cdef59f7bc4a","target":"graph","created_at":"2026-07-05T03:08:43Z","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/2010.03255/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-grained few-shot recognition often suffers from the problem of training data scarcity for novel categories.The network tends to overfit and does not generalize well to unseen classes due to insufficient training data. Many methods have been proposed to synthesize additional data to support the training. In this paper, we focus one enlarging the intra-class variance of the unseen class to improve few-shot classification performance. We assume that the distribution of intra-class variance generalizes across the base class and the novel class. Thus, the intra-class variance of the base set c","authors_text":"Dimitris Samaras, Hieu Le, Jingyi Xu, Mingzhen Huang, ShahRukh Athar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-07T08:13:42Z","title":"Variational Feature Disentangling for Fine-Grained Few-Shot Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.03255","kind":"arxiv","version":3},"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:f7f8fc628c9f2a6e188b67c873eeb90a560339a601a375c946813d016b464147","target":"record","created_at":"2026-07-05T03:08:43Z","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":"52537e951804da63f55a914d6965e395b3bd94bfc324e9961d22b0bba0f999dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-07T08:13:42Z","title_canon_sha256":"b97bc26da7eb1cf00aa8e6be1fe4dcc5d70ea8a322c324ff19a99436d1c4750a"},"schema_version":"1.0","source":{"id":"2010.03255","kind":"arxiv","version":3}},"canonical_sha256":"5d37d89033bda4051a7e467f6985cd6f42eaab36b88577ebc6ec8179d39a5803","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d37d89033bda4051a7e467f6985cd6f42eaab36b88577ebc6ec8179d39a5803","first_computed_at":"2026-07-05T03:08:43.009384Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:08:43.009384Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"unL+U/eVgrl4Y7SwXvbWVi8aTrgpPcD+NYxSzjkCWIja0v9Z0AvEZvqt/JhZkrdQNIb7tYoHkwDr+0aV7N1XAw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:08:43.009758Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.03255","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f7f8fc628c9f2a6e188b67c873eeb90a560339a601a375c946813d016b464147","sha256:a1515c329fc1d274ebf185a6f5eae042bce014fb2f62a2529cd5cdef59f7bc4a"],"state_sha256":"a2c3b3e02170c126db7f4ca30179aed71ca08fc58e3c421b21e716cdc7021085"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OCZ3b5Mb+X1724iBhYZEiSC/Wf/3soFovl+tmBvz7ikOdj7WiJeWhK+7q2KFx2voogzJZ0TbTqbpj8mYOCmJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T11:28:09.286049Z","bundle_sha256":"682f94ca7fc0610d6e8fb83c5edb7914a5cd1e69c1d391f071d6c1d6bb00d4c6"}}