{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:5K7OL3U4PAAS5WXIXHI3N5LFQQ","short_pith_number":"pith:5K7OL3U4","canonical_record":{"source":{"id":"1812.03664","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-10T07:55:56Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"62c3ee3de3bf0cdb36e95c1173630e01f59a79c598ea36c740a4514231e02cce","abstract_canon_sha256":"960195f1d9e57f4c970a4fcbdb814b078f2333a71fcaecb11919855c9a02a581"},"schema_version":"1.0"},"canonical_sha256":"eabee5ee9c78012edae8b9d1b6f565841f2a91089dd868d10741a5e35b9579e5","source":{"kind":"arxiv","id":"1812.03664","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03664","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03664v6","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03664","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_12","alias_value":"5K7OL3U4PAAS","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_16","alias_value":"5K7OL3U4PAAS5WXI","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_8","alias_value":"5K7OL3U4","created_at":"2026-07-05T02:48:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:5K7OL3U4PAAS5WXIXHI3N5LFQQ","target":"record","payload":{"canonical_record":{"source":{"id":"1812.03664","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-10T07:55:56Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"62c3ee3de3bf0cdb36e95c1173630e01f59a79c598ea36c740a4514231e02cce","abstract_canon_sha256":"960195f1d9e57f4c970a4fcbdb814b078f2333a71fcaecb11919855c9a02a581"},"schema_version":"1.0"},"canonical_sha256":"eabee5ee9c78012edae8b9d1b6f565841f2a91089dd868d10741a5e35b9579e5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:48:31.517807Z","signature_b64":"oIPstKYiqjAD/fyI5wdFuIYDqTIOyA6ikaY8ykUWT4897krwISnDmAR6CoWRx84ZXzIq9G1lmnc84FUb61PrAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eabee5ee9c78012edae8b9d1b6f565841f2a91089dd868d10741a5e35b9579e5","last_reissued_at":"2026-07-05T02:48:31.517339Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:48:31.517339Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.03664","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:48:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YtsNg7ETuaayH4n0nIwUeKjLNKucWEc8V94ktNubmrAa5z0urwQRcRxVa8AmEoG3NN8o5lfmr2SWM8z6ZIH0CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:55:15.288329Z"},"content_sha256":"2ee28158177f83394f73bd747f1204c22188377ed4cd6b43f530eb8f4cf4605f","schema_version":"1.0","event_id":"sha256:2ee28158177f83394f73bd747f1204c22188377ed4cd6b43f530eb8f4cf4605f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:5K7OL3U4PAAS5WXIXHI3N5LFQQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"De-Chuan Zhan, Fei Sha, Han-Jia Ye, Hexiang Hu","submitted_at":"2018-12-10T07:55:56Z","abstract_excerpt":"Learning with limited data is a key challenge for visual recognition. Many few-shot learning methods address this challenge by learning an instance embedding function from seen classes and apply the function to instances from unseen classes with limited labels. This style of transfer learning is task-agnostic: the embedding function is not learned optimally discriminative with respect to the unseen classes, where discerning among them leads to the target task. In this paper, we propose a novel approach to adapt the instance embeddings to the target classification task with a set-to-set functio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03664","kind":"arxiv","version":6},"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/1812.03664/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":"2026-07-05T02:48:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gqlH/7mnKGWTdXb/0lCSok/F/F9fbqSuSY89owlQgs56VRPZsXLOcjT3vGhLK/rJlFVG9brJ++96B6iYvm+nBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T19:55:15.288871Z"},"content_sha256":"b11ef051fd500a46c3a7e44e97d8c1d1aca57a56d4d907bd17b4194ec45599a3","schema_version":"1.0","event_id":"sha256:b11ef051fd500a46c3a7e44e97d8c1d1aca57a56d4d907bd17b4194ec45599a3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/bundle.json","state_url":"https://pith.science/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/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":"2026-08-07T19:55:15Z","links":{"resolver":"https://pith.science/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ","bundle":"https://pith.science/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/bundle.json","state":"https://pith.science/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5K7OL3U4PAAS5WXIXHI3N5LFQQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:5K7OL3U4PAAS5WXIXHI3N5LFQQ","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":"960195f1d9e57f4c970a4fcbdb814b078f2333a71fcaecb11919855c9a02a581","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-10T07:55:56Z","title_canon_sha256":"62c3ee3de3bf0cdb36e95c1173630e01f59a79c598ea36c740a4514231e02cce"},"schema_version":"1.0","source":{"id":"1812.03664","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03664","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03664v6","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03664","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_12","alias_value":"5K7OL3U4PAAS","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_16","alias_value":"5K7OL3U4PAAS5WXI","created_at":"2026-07-05T02:48:31Z"},{"alias_kind":"pith_short_8","alias_value":"5K7OL3U4","created_at":"2026-07-05T02:48:31Z"}],"graph_snapshots":[{"event_id":"sha256:b11ef051fd500a46c3a7e44e97d8c1d1aca57a56d4d907bd17b4194ec45599a3","target":"graph","created_at":"2026-07-05T02:48:31Z","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/1812.03664/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning with limited data is a key challenge for visual recognition. Many few-shot learning methods address this challenge by learning an instance embedding function from seen classes and apply the function to instances from unseen classes with limited labels. This style of transfer learning is task-agnostic: the embedding function is not learned optimally discriminative with respect to the unseen classes, where discerning among them leads to the target task. In this paper, we propose a novel approach to adapt the instance embeddings to the target classification task with a set-to-set functio","authors_text":"De-Chuan Zhan, Fei Sha, Han-Jia Ye, Hexiang Hu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-10T07:55:56Z","title":"Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03664","kind":"arxiv","version":6},"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":"sha256:2ee28158177f83394f73bd747f1204c22188377ed4cd6b43f530eb8f4cf4605f","target":"record","created_at":"2026-07-05T02:48:31Z","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":"960195f1d9e57f4c970a4fcbdb814b078f2333a71fcaecb11919855c9a02a581","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-12-10T07:55:56Z","title_canon_sha256":"62c3ee3de3bf0cdb36e95c1173630e01f59a79c598ea36c740a4514231e02cce"},"schema_version":"1.0","source":{"id":"1812.03664","kind":"arxiv","version":6}},"canonical_sha256":"eabee5ee9c78012edae8b9d1b6f565841f2a91089dd868d10741a5e35b9579e5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eabee5ee9c78012edae8b9d1b6f565841f2a91089dd868d10741a5e35b9579e5","first_computed_at":"2026-07-05T02:48:31.517339Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:48:31.517339Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oIPstKYiqjAD/fyI5wdFuIYDqTIOyA6ikaY8ykUWT4897krwISnDmAR6CoWRx84ZXzIq9G1lmnc84FUb61PrAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:48:31.517807Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.03664","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2ee28158177f83394f73bd747f1204c22188377ed4cd6b43f530eb8f4cf4605f","sha256:b11ef051fd500a46c3a7e44e97d8c1d1aca57a56d4d907bd17b4194ec45599a3"],"state_sha256":"ebac4270d758f203c60954fa3c465ab488dd671f2068510e3c76f7a8313b8b26"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EkO/0l0n4PnoMiY8KENlyIryg8uC10oIUVMQ2lf8yn7NOkc+Jp1yNA1F/kzV11VerD8ScJVTtCRUeWSQsSFSAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T19:55:15.292875Z","bundle_sha256":"c7d95be124325bfbd2610b1c4fe0084870ac4c2a23121319de807667540a37b4"}}