{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:DDPJFQUKJET7EI3SZM6RTF2G4F","short_pith_number":"pith:DDPJFQUK","canonical_record":{"source":{"id":"2010.01773","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-05T04:41:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"099ed47359657463e7e19c7cab4c9d4151b03e19f412865ae3d352d9a24ef15a","abstract_canon_sha256":"4ccb29e6cea7b624bc7064c1e534f95677934ee10fec705722ba27361442bb8c"},"schema_version":"1.0"},"canonical_sha256":"18de92c28a4927f22372cb3d199746e140fe79fa1d7671cd439102f41f91ff06","source":{"kind":"arxiv","id":"2010.01773","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.01773","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"arxiv_version","alias_value":"2010.01773v3","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.01773","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_12","alias_value":"DDPJFQUKJET7","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_16","alias_value":"DDPJFQUKJET7EI3S","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_8","alias_value":"DDPJFQUK","created_at":"2026-07-05T02:20:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:DDPJFQUKJET7EI3SZM6RTF2G4F","target":"record","payload":{"canonical_record":{"source":{"id":"2010.01773","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-05T04:41:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"099ed47359657463e7e19c7cab4c9d4151b03e19f412865ae3d352d9a24ef15a","abstract_canon_sha256":"4ccb29e6cea7b624bc7064c1e534f95677934ee10fec705722ba27361442bb8c"},"schema_version":"1.0"},"canonical_sha256":"18de92c28a4927f22372cb3d199746e140fe79fa1d7671cd439102f41f91ff06","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:20:42.298814Z","signature_b64":"ZYBY+RWRaQCwMbdA9k0zUpkaEHMqXBXCsmaZcy2iP4+kYL/xb0mdukZJvXSX4Rq1xKR4N7750hXz+r9HGeAiAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18de92c28a4927f22372cb3d199746e140fe79fa1d7671cd439102f41f91ff06","last_reissued_at":"2026-07-05T02:20:42.298429Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:20:42.298429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.01773","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":"2026-07-05T02:20:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eaf2rC5ufzxJF3l02RmLEFLo4Op5JKhIQOQcRaupNgaIqZmVIVuTR3zQ8Jg3gFgGLdSN53u6tjAxAv8uPSWrAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T02:26:46.689316Z"},"content_sha256":"a023a883f4b223a0117260cf1ed84af2c45281861d18e47337c592ed18d2e33f","schema_version":"1.0","event_id":"sha256:a023a883f4b223a0117260cf1ed84af2c45281861d18e47337c592ed18d2e33f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:DDPJFQUKJET7EI3SZM6RTF2G4F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Daniel McDuff, Josh Fromm, Shwetak Patel, Xin Liu, Xuhai Xu, Ziheng Jiang","submitted_at":"2020-10-05T04:41:03Z","abstract_excerpt":"There are large individual differences in physiological processes, making designing personalized health sensing algorithms challenging. Existing machine learning systems struggle to generalize well to unseen subjects or contexts and can often contain problematic biases. Video-based physiological measurement is not an exception. Therefore, learning personalized or customized models from a small number of unlabeled samples is very attractive as it would allow fast calibrations to improve generalization and help correct biases. In this paper, we present a novel meta-learning approach called MetaP"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.01773","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/2010.01773/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":"2026-07-05T02:20:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ums6Fk5FakSxeQ3e1dtuBb6aeapOiGrcSmJgOKA4aYcHiD8BZOjMwUn5k9C8v/GCf1rNaFpl/QKMcq55v5fGBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T02:26:46.690203Z"},"content_sha256":"69460daeb2304e70be12d72f9c0953bf3e7de1a36d073f836962e23661e43c0b","schema_version":"1.0","event_id":"sha256:69460daeb2304e70be12d72f9c0953bf3e7de1a36d073f836962e23661e43c0b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/bundle.json","state_url":"https://pith.science/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/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":"2026-08-18T02:26:46Z","links":{"resolver":"https://pith.science/pith/DDPJFQUKJET7EI3SZM6RTF2G4F","bundle":"https://pith.science/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/bundle.json","state":"https://pith.science/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DDPJFQUKJET7EI3SZM6RTF2G4F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:DDPJFQUKJET7EI3SZM6RTF2G4F","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":"4ccb29e6cea7b624bc7064c1e534f95677934ee10fec705722ba27361442bb8c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-05T04:41:03Z","title_canon_sha256":"099ed47359657463e7e19c7cab4c9d4151b03e19f412865ae3d352d9a24ef15a"},"schema_version":"1.0","source":{"id":"2010.01773","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.01773","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"arxiv_version","alias_value":"2010.01773v3","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.01773","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_12","alias_value":"DDPJFQUKJET7","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_16","alias_value":"DDPJFQUKJET7EI3S","created_at":"2026-07-05T02:20:42Z"},{"alias_kind":"pith_short_8","alias_value":"DDPJFQUK","created_at":"2026-07-05T02:20:42Z"}],"graph_snapshots":[{"event_id":"sha256:69460daeb2304e70be12d72f9c0953bf3e7de1a36d073f836962e23661e43c0b","target":"graph","created_at":"2026-07-05T02:20:42Z","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/2010.01773/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There are large individual differences in physiological processes, making designing personalized health sensing algorithms challenging. Existing machine learning systems struggle to generalize well to unseen subjects or contexts and can often contain problematic biases. Video-based physiological measurement is not an exception. Therefore, learning personalized or customized models from a small number of unlabeled samples is very attractive as it would allow fast calibrations to improve generalization and help correct biases. In this paper, we present a novel meta-learning approach called MetaP","authors_text":"Daniel McDuff, Josh Fromm, Shwetak Patel, Xin Liu, Xuhai Xu, Ziheng Jiang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-05T04:41:03Z","title":"MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.01773","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:a023a883f4b223a0117260cf1ed84af2c45281861d18e47337c592ed18d2e33f","target":"record","created_at":"2026-07-05T02:20:42Z","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":"4ccb29e6cea7b624bc7064c1e534f95677934ee10fec705722ba27361442bb8c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-05T04:41:03Z","title_canon_sha256":"099ed47359657463e7e19c7cab4c9d4151b03e19f412865ae3d352d9a24ef15a"},"schema_version":"1.0","source":{"id":"2010.01773","kind":"arxiv","version":3}},"canonical_sha256":"18de92c28a4927f22372cb3d199746e140fe79fa1d7671cd439102f41f91ff06","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"18de92c28a4927f22372cb3d199746e140fe79fa1d7671cd439102f41f91ff06","first_computed_at":"2026-07-05T02:20:42.298429Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:20:42.298429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZYBY+RWRaQCwMbdA9k0zUpkaEHMqXBXCsmaZcy2iP4+kYL/xb0mdukZJvXSX4Rq1xKR4N7750hXz+r9HGeAiAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:20:42.298814Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.01773","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a023a883f4b223a0117260cf1ed84af2c45281861d18e47337c592ed18d2e33f","sha256:69460daeb2304e70be12d72f9c0953bf3e7de1a36d073f836962e23661e43c0b"],"state_sha256":"17bef97b573ae9282515da28cfe1a872b59d056f6cf1e553ca2bf59d53fe9341"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H4EcbqhNzoZhvEsZT9zPjyXwVz8XEQbZJ63J8m0NQutrZtzVVMbnYwViXXBl4eFrsKeMTGceYN0Nn1OnrC1pDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T02:26:46.695622Z","bundle_sha256":"6513115bbe8bf64405a96ddf297fd5cb821dcc08a6c37bfd9f94f3ceae63aa5a"}}