{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ","short_pith_number":"pith:ZHYJ7ZAO","canonical_record":{"source":{"id":"2205.04771","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-10T09:49:40Z","cross_cats_sorted":[],"title_canon_sha256":"8818ef999380f6e3a0cde606fa6cac428e4413a4d78bb61ad0d738080182662c","abstract_canon_sha256":"719a759b95879fd9322d2e8b250494fa43af78de78603fe5c1abaed3c939771f"},"schema_version":"1.0"},"canonical_sha256":"c9f09fe40eba7930cb06a968292f16b64dd7c1d6c31535e13eff980abbbe39eb","source":{"kind":"arxiv","id":"2205.04771","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.04771","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"arxiv_version","alias_value":"2205.04771v2","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.04771","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_12","alias_value":"ZHYJ7ZAOXJ4T","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_16","alias_value":"ZHYJ7ZAOXJ4TBSYG","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_8","alias_value":"ZHYJ7ZAO","created_at":"2026-07-05T04:29:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ","target":"record","payload":{"canonical_record":{"source":{"id":"2205.04771","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-10T09:49:40Z","cross_cats_sorted":[],"title_canon_sha256":"8818ef999380f6e3a0cde606fa6cac428e4413a4d78bb61ad0d738080182662c","abstract_canon_sha256":"719a759b95879fd9322d2e8b250494fa43af78de78603fe5c1abaed3c939771f"},"schema_version":"1.0"},"canonical_sha256":"c9f09fe40eba7930cb06a968292f16b64dd7c1d6c31535e13eff980abbbe39eb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:29:13.659397Z","signature_b64":"+68U7en/+EVhUxt6cu2D/dDivA9BQPgZedm3Ua1tEDEv4XO7q0nQpD2/lrwNUJT1qVY5iJsVmxZM/B63X/juDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9f09fe40eba7930cb06a968292f16b64dd7c1d6c31535e13eff980abbbe39eb","last_reissued_at":"2026-07-05T04:29:13.658987Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:29:13.658987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.04771","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:29:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E+9hedxbBOOWk8bbzUuFeMF1T7omaFllTXDC1XfjhX9u/Nu+2ZxR1uDx3kRtIeHz07mAyLs4HR/9nBhG+nThDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T07:22:07.866158Z"},"content_sha256":"c3028570f61854e3e04500772bee82de6476195b476876c9bf31472e4c8f7a32","schema_version":"1.0","event_id":"sha256:c3028570f61854e3e04500772bee82de6476195b476876c9bf31472e4c8f7a32"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Feng Zhu, Haiyang Yang, Lei Bai, Meilin Chen, Rui Zhao, Shixiang Tang, Wanli Ouyang, Yizhou Wang","submitted_at":"2022-05-10T09:49:40Z","abstract_excerpt":"Generalizing learned representations across significantly different visual domains is a fundamental yet crucial ability of the human visual system. While recent self-supervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain. Therefore, the self-supervised learning from multiple domains task is proposed to learn domain-invariant features that are not only suitable for evaluation on the same domain as the training set but also can be generalized to un"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.04771","kind":"arxiv","version":2},"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/2205.04771/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":"2026-07-05T04:29:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iakl7eQrrEVW/Fx+xuqVR57yuUySUTf1MFNRwMrbFS4gDAXXqFGvo4vZZt6NMiR1S10sbyarNKI43XlhLnFxCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T07:22:07.866691Z"},"content_sha256":"724b32a4564436352cc7f2cfe0bebc041ef90057806b482fd0c0225c30d178a0","schema_version":"1.0","event_id":"sha256:724b32a4564436352cc7f2cfe0bebc041ef90057806b482fd0c0225c30d178a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/bundle.json","state_url":"https://pith.science/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/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":"2026-08-01T07:22:07Z","links":{"resolver":"https://pith.science/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ","bundle":"https://pith.science/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/bundle.json","state":"https://pith.science/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ZHYJ7ZAOXJ4TBSYGVFUCSLYWWZ","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":"719a759b95879fd9322d2e8b250494fa43af78de78603fe5c1abaed3c939771f","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-10T09:49:40Z","title_canon_sha256":"8818ef999380f6e3a0cde606fa6cac428e4413a4d78bb61ad0d738080182662c"},"schema_version":"1.0","source":{"id":"2205.04771","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.04771","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"arxiv_version","alias_value":"2205.04771v2","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.04771","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_12","alias_value":"ZHYJ7ZAOXJ4T","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_16","alias_value":"ZHYJ7ZAOXJ4TBSYG","created_at":"2026-07-05T04:29:13Z"},{"alias_kind":"pith_short_8","alias_value":"ZHYJ7ZAO","created_at":"2026-07-05T04:29:13Z"}],"graph_snapshots":[{"event_id":"sha256:724b32a4564436352cc7f2cfe0bebc041ef90057806b482fd0c0225c30d178a0","target":"graph","created_at":"2026-07-05T04:29:13Z","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/2205.04771/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generalizing learned representations across significantly different visual domains is a fundamental yet crucial ability of the human visual system. While recent self-supervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain. Therefore, the self-supervised learning from multiple domains task is proposed to learn domain-invariant features that are not only suitable for evaluation on the same domain as the training set but also can be generalized to un","authors_text":"Feng Zhu, Haiyang Yang, Lei Bai, Meilin Chen, Rui Zhao, Shixiang Tang, Wanli Ouyang, Yizhou Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-10T09:49:40Z","title":"Domain Invariant Masked Autoencoders for Self-supervised Learning from Multi-domains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.04771","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:c3028570f61854e3e04500772bee82de6476195b476876c9bf31472e4c8f7a32","target":"record","created_at":"2026-07-05T04:29:13Z","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":"719a759b95879fd9322d2e8b250494fa43af78de78603fe5c1abaed3c939771f","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2022-05-10T09:49:40Z","title_canon_sha256":"8818ef999380f6e3a0cde606fa6cac428e4413a4d78bb61ad0d738080182662c"},"schema_version":"1.0","source":{"id":"2205.04771","kind":"arxiv","version":2}},"canonical_sha256":"c9f09fe40eba7930cb06a968292f16b64dd7c1d6c31535e13eff980abbbe39eb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9f09fe40eba7930cb06a968292f16b64dd7c1d6c31535e13eff980abbbe39eb","first_computed_at":"2026-07-05T04:29:13.658987Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:29:13.658987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+68U7en/+EVhUxt6cu2D/dDivA9BQPgZedm3Ua1tEDEv4XO7q0nQpD2/lrwNUJT1qVY5iJsVmxZM/B63X/juDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:29:13.659397Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.04771","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c3028570f61854e3e04500772bee82de6476195b476876c9bf31472e4c8f7a32","sha256:724b32a4564436352cc7f2cfe0bebc041ef90057806b482fd0c0225c30d178a0"],"state_sha256":"33aba354881af449c2b55dbc5504bb127535a01258f60de2b5208cbe0b2ee267"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BxK0aSyCmOkqsXyJJk+qYd9Qm5bH1gpgAafM1ldUkdEnMK37I0VKe3ciZg+nWV0+K4NBXQqWu16Zic8MA77nDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T07:22:07.872108Z","bundle_sha256":"c8a67d9d5eee8d9b0e56468df63ca13046df122606a234529f3d8b19cd88ffe3"}}