{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:KP3OOYUGJBEKFJQIHRDOCYYJDO","short_pith_number":"pith:KP3OOYUG","canonical_record":{"source":{"id":"2103.09027","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-16T12:53:09Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ae2f1b2a75b5d6d35b0c7506b262d0832dc2580a24d85b1c96e4d7503108d00c","abstract_canon_sha256":"635652d3817be9ab3601e717f8a1e5f904fd61d687d5957fcde7069dc1549f1e"},"schema_version":"1.0"},"canonical_sha256":"53f6e762864848a2a6083c46e163091b8edb8e69f3a81e278fb0cc0e91d78d36","source":{"kind":"arxiv","id":"2103.09027","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.09027","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"arxiv_version","alias_value":"2103.09027v1","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.09027","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_12","alias_value":"KP3OOYUGJBEK","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_16","alias_value":"KP3OOYUGJBEKFJQI","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_8","alias_value":"KP3OOYUG","created_at":"2026-07-05T02:23:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:KP3OOYUGJBEKFJQIHRDOCYYJDO","target":"record","payload":{"canonical_record":{"source":{"id":"2103.09027","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-16T12:53:09Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ae2f1b2a75b5d6d35b0c7506b262d0832dc2580a24d85b1c96e4d7503108d00c","abstract_canon_sha256":"635652d3817be9ab3601e717f8a1e5f904fd61d687d5957fcde7069dc1549f1e"},"schema_version":"1.0"},"canonical_sha256":"53f6e762864848a2a6083c46e163091b8edb8e69f3a81e278fb0cc0e91d78d36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:23:34.381327Z","signature_b64":"7npdZP6TWpWkV6QJXFagVOwW0JREZLHMRXw33PN0lKcgzgzC3yjCWFp/UEGvievxJaCuWQjFr/0K5pEE/ryFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"53f6e762864848a2a6083c46e163091b8edb8e69f3a81e278fb0cc0e91d78d36","last_reissued_at":"2026-07-05T02:23:34.380969Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:23:34.380969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2103.09027","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":"2026-07-05T02:23:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ae2tLz8phRc6y2EHDbYnve9bnxF96fyXD6q3lxR/QLcVj+jkImL0HL/d5vpZzS0HZDjbLd5KjQev3lWq/y/7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T04:14:53.777185Z"},"content_sha256":"60b96d582f0e2b86ae17fc79fb3215621ec814e898e4cb5d6af77b024e3b8ac8","schema_version":"1.0","event_id":"sha256:60b96d582f0e2b86ae17fc79fb3215621ec814e898e4cb5d6af77b024e3b8ac8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:KP3OOYUGJBEKFJQIHRDOCYYJDO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Gabriel Huang, Hwidong Na, Namyeong Kwon, Simon Lacoste-Julien","submitted_at":"2021-03-16T12:53:09Z","abstract_excerpt":"Model-agnostic meta-learning (MAML) is a popular method for few-shot learning but assumes that we have access to the meta-training set. In practice, training on the meta-training set may not always be an option due to data privacy concerns, intellectual property issues, or merely lack of computing resources. In this paper, we consider the novel problem of repurposing pretrained MAML checkpoints to solve new few-shot classification tasks. Because of the potential distribution mismatch, the original MAML steps may no longer be optimal. Therefore we propose an alternative meta-testing procedure a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.09027","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/2103.09027/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":"2026-07-05T02:23:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vb3dgHgzYjukhyN+w64zRjXQHMQ7/sU8PDhxMZph6pNqK0Kh9jCk/g7ohzBiMtSxkf0RkuTzhp+eLXD3lv8aCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-24T04:14:53.777695Z"},"content_sha256":"89b83dcbc3986393635822ed81fdbf00a6c22d8828f7e3c0185590cf87966385","schema_version":"1.0","event_id":"sha256:89b83dcbc3986393635822ed81fdbf00a6c22d8828f7e3c0185590cf87966385"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/bundle.json","state_url":"https://pith.science/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/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":"2026-08-24T04:14:53Z","links":{"resolver":"https://pith.science/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO","bundle":"https://pith.science/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/bundle.json","state":"https://pith.science/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KP3OOYUGJBEKFJQIHRDOCYYJDO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:KP3OOYUGJBEKFJQIHRDOCYYJDO","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":"635652d3817be9ab3601e717f8a1e5f904fd61d687d5957fcde7069dc1549f1e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-16T12:53:09Z","title_canon_sha256":"ae2f1b2a75b5d6d35b0c7506b262d0832dc2580a24d85b1c96e4d7503108d00c"},"schema_version":"1.0","source":{"id":"2103.09027","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.09027","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"arxiv_version","alias_value":"2103.09027v1","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.09027","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_12","alias_value":"KP3OOYUGJBEK","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_16","alias_value":"KP3OOYUGJBEKFJQI","created_at":"2026-07-05T02:23:34Z"},{"alias_kind":"pith_short_8","alias_value":"KP3OOYUG","created_at":"2026-07-05T02:23:34Z"}],"graph_snapshots":[{"event_id":"sha256:89b83dcbc3986393635822ed81fdbf00a6c22d8828f7e3c0185590cf87966385","target":"graph","created_at":"2026-07-05T02:23:34Z","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/2103.09027/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model-agnostic meta-learning (MAML) is a popular method for few-shot learning but assumes that we have access to the meta-training set. In practice, training on the meta-training set may not always be an option due to data privacy concerns, intellectual property issues, or merely lack of computing resources. In this paper, we consider the novel problem of repurposing pretrained MAML checkpoints to solve new few-shot classification tasks. Because of the potential distribution mismatch, the original MAML steps may no longer be optimal. Therefore we propose an alternative meta-testing procedure a","authors_text":"Gabriel Huang, Hwidong Na, Namyeong Kwon, Simon Lacoste-Julien","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-16T12:53:09Z","title":"Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.09027","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":"sha256:60b96d582f0e2b86ae17fc79fb3215621ec814e898e4cb5d6af77b024e3b8ac8","target":"record","created_at":"2026-07-05T02:23:34Z","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":"635652d3817be9ab3601e717f8a1e5f904fd61d687d5957fcde7069dc1549f1e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-03-16T12:53:09Z","title_canon_sha256":"ae2f1b2a75b5d6d35b0c7506b262d0832dc2580a24d85b1c96e4d7503108d00c"},"schema_version":"1.0","source":{"id":"2103.09027","kind":"arxiv","version":1}},"canonical_sha256":"53f6e762864848a2a6083c46e163091b8edb8e69f3a81e278fb0cc0e91d78d36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53f6e762864848a2a6083c46e163091b8edb8e69f3a81e278fb0cc0e91d78d36","first_computed_at":"2026-07-05T02:23:34.380969Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:23:34.380969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7npdZP6TWpWkV6QJXFagVOwW0JREZLHMRXw33PN0lKcgzgzC3yjCWFp/UEGvievxJaCuWQjFr/0K5pEE/ryFBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:23:34.381327Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.09027","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60b96d582f0e2b86ae17fc79fb3215621ec814e898e4cb5d6af77b024e3b8ac8","sha256:89b83dcbc3986393635822ed81fdbf00a6c22d8828f7e3c0185590cf87966385"],"state_sha256":"5eba563f507cde2ac9ca07f260e97e28270fc3e3d4745e26995d0cb5796d9fa4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xolvmq+Q+0AuB+FRv8eFMUhORM/eB8muWSIfn/6T3nlbwB5I/yv1QGGqMYpwZfbK7tGnx1jKybc6cYtrHqP7CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-24T04:14:53.782600Z","bundle_sha256":"0652249efe73dbe32d2ea02324a28ec2fe89cb7eb9aa9c3a056751905d5af5e3"}}