{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:N7VYYNQUFQCXVAZJCEGP2QWFK5","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":"808da2273dad9a05b846bc20027af18d13ef497e594d5c8561cb02a3d588d961","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-13T07:41:56Z","title_canon_sha256":"69dfc19e6c0ba51753955a61b06209d02ea86a34725ed931e3ca2aba0f4afe75"},"schema_version":"1.0","source":{"id":"2004.05805","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.05805","created_at":"2026-07-05T01:35:57Z"},{"alias_kind":"arxiv_version","alias_value":"2004.05805v2","created_at":"2026-07-05T01:35:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.05805","created_at":"2026-07-05T01:35:57Z"},{"alias_kind":"pith_short_12","alias_value":"N7VYYNQUFQCX","created_at":"2026-07-05T01:35:57Z"},{"alias_kind":"pith_short_16","alias_value":"N7VYYNQUFQCXVAZJ","created_at":"2026-07-05T01:35:57Z"},{"alias_kind":"pith_short_8","alias_value":"N7VYYNQU","created_at":"2026-07-05T01:35:57Z"}],"graph_snapshots":[{"event_id":"sha256:0365d8d8d6ba70309d0ade2b781c0a06f8d910b9be9857df2b643ed3280e1434","target":"graph","created_at":"2026-07-05T01:35:57Z","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/2004.05805/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-shot learning aims to learn a new concept when only a few training examples are available, which has been extensively explored in recent years. However, most of the current works heavily rely on a large-scale labeled auxiliary set to train their models in an episodic-training paradigm. Such a kind of supervised setting basically limits the widespread use of few-shot learning algorithms. Instead, in this paper, we develop a novel framework called Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation (ULDA), which pays attention to the distribution diversity inside ea","authors_text":"Tiexin Qin, Wenbin Li, Yang Gao, Yinghuan Shi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-13T07:41:56Z","title":"Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.05805","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:c0f260ba047d153ef08ff9ce9f20ba9388313522beee8bfff64e0f33eef598cf","target":"record","created_at":"2026-07-05T01:35:57Z","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":"808da2273dad9a05b846bc20027af18d13ef497e594d5c8561cb02a3d588d961","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-04-13T07:41:56Z","title_canon_sha256":"69dfc19e6c0ba51753955a61b06209d02ea86a34725ed931e3ca2aba0f4afe75"},"schema_version":"1.0","source":{"id":"2004.05805","kind":"arxiv","version":2}},"canonical_sha256":"6feb8c36142c057a8329110cfd42c5576638b79bf560780741d91dd43c52259a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6feb8c36142c057a8329110cfd42c5576638b79bf560780741d91dd43c52259a","first_computed_at":"2026-07-05T01:35:57.668493Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:35:57.668493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KPs6t7IhLj2hPXDeVVhEFwMQUM2LEA0s7P+rayfg+2QaJw7zG6baB9vUvQX7WuYbUKp7FpaYjoMVcP0OplYjCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:35:57.668891Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.05805","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0f260ba047d153ef08ff9ce9f20ba9388313522beee8bfff64e0f33eef598cf","sha256:0365d8d8d6ba70309d0ade2b781c0a06f8d910b9be9857df2b643ed3280e1434"],"state_sha256":"40edcf20721eb57829270449b9f954452e772808f80b74b1bdca6e03846bc16b"}