{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:VKXYI63A77UH5FFSCYOXL5CDDM","short_pith_number":"pith:VKXYI63A","canonical_record":{"source":{"id":"2207.01066","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-03T15:24:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"e44d05a91ee152640284778b1f6e56895c921a50cf9dd5e4f4b9c7e436324b9a","abstract_canon_sha256":"7b1369d5ff674679f537c0736a1755b4b3ca0cd5e0251eaaac655d4dfb627ce7"},"schema_version":"1.0"},"canonical_sha256":"aaaf847b60ffe87e94b2161d75f4431b33d585d1d14fd0a378b1a6f2795dd678","source":{"kind":"arxiv","id":"2207.01066","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01066","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01066v1","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01066","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_12","alias_value":"VKXYI63A77UH","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_16","alias_value":"VKXYI63A77UH5FFS","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_8","alias_value":"VKXYI63A","created_at":"2026-07-05T04:37:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:VKXYI63A77UH5FFSCYOXL5CDDM","target":"record","payload":{"canonical_record":{"source":{"id":"2207.01066","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-03T15:24:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"e44d05a91ee152640284778b1f6e56895c921a50cf9dd5e4f4b9c7e436324b9a","abstract_canon_sha256":"7b1369d5ff674679f537c0736a1755b4b3ca0cd5e0251eaaac655d4dfb627ce7"},"schema_version":"1.0"},"canonical_sha256":"aaaf847b60ffe87e94b2161d75f4431b33d585d1d14fd0a378b1a6f2795dd678","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:37:07.537251Z","signature_b64":"/xu7Jm7VoulJrjw9Btg5rI5iCeD26gGLZtuTEA+6AOiVKGZAIO2iEzPNMEeWZkU/pdjnM4HLMbnkusFUnZ3oAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aaaf847b60ffe87e94b2161d75f4431b33d585d1d14fd0a378b1a6f2795dd678","last_reissued_at":"2026-07-05T04:37:07.536834Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:37:07.536834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.01066","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":"2026-07-05T04:37:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0pXl1eU5jm1al2U6RjbdOlhEM9z+pnMDGiOooESzpZ/DxRanWkC2Eb98ibjkguJfthDmC0iB4r8PEUqpRUFBBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-21T06:58:47.295688Z"},"content_sha256":"741784be77a583c9ca6fb8a75f0e4c28c34b9cb36ea65336a87787eb61cbfce0","schema_version":"1.0","event_id":"sha256:741784be77a583c9ca6fb8a75f0e4c28c34b9cb36ea65336a87787eb61cbfce0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:VKXYI63A77UH5FFSCYOXL5CDDM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NP-Match: When Neural Processes meet Semi-Supervised Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Alexandros Neophytou, Daniela Massiceti, Jianfeng Wang, Thomas Lukasiewicz, Vladimir Pavlovic, Xiaolin Hu","submitted_at":"2022-07-03T15:24:31Z","abstract_excerpt":"Semi-supervised learning (SSL) has been widely explored in recent years, and it is an effective way of leveraging unlabeled data to reduce the reliance on labeled data. In this work, we adjust neural processes (NPs) to the semi-supervised image classification task, resulting in a new method named NP-Match. NP-Match is suited to this task for two reasons. Firstly, NP-Match implicitly compares data points when making predictions, and as a result, the prediction of each unlabeled data point is affected by the labeled data points that are similar to it, which improves the quality of pseudo-labels."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01066","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/2207.01066/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":"2026-07-05T04:37:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t7c11FQz1oav0XG8JeNxaXoYQ1EZXouHK2SUI/eHnJBG1ZDk4aT5UlvFW8UHzLHkCIKvlBqe+95AB3SPxNr6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-21T06:58:47.296081Z"},"content_sha256":"b9fd73aff0489320b3cfb317b6be1afa299310217be30f664b56f4b268e1e4c8","schema_version":"1.0","event_id":"sha256:b9fd73aff0489320b3cfb317b6be1afa299310217be30f664b56f4b268e1e4c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VKXYI63A77UH5FFSCYOXL5CDDM/bundle.json","state_url":"https://pith.science/pith/VKXYI63A77UH5FFSCYOXL5CDDM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VKXYI63A77UH5FFSCYOXL5CDDM/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":"2026-07-21T06:58:47Z","links":{"resolver":"https://pith.science/pith/VKXYI63A77UH5FFSCYOXL5CDDM","bundle":"https://pith.science/pith/VKXYI63A77UH5FFSCYOXL5CDDM/bundle.json","state":"https://pith.science/pith/VKXYI63A77UH5FFSCYOXL5CDDM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VKXYI63A77UH5FFSCYOXL5CDDM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VKXYI63A77UH5FFSCYOXL5CDDM","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":"7b1369d5ff674679f537c0736a1755b4b3ca0cd5e0251eaaac655d4dfb627ce7","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-03T15:24:31Z","title_canon_sha256":"e44d05a91ee152640284778b1f6e56895c921a50cf9dd5e4f4b9c7e436324b9a"},"schema_version":"1.0","source":{"id":"2207.01066","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.01066","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"arxiv_version","alias_value":"2207.01066v1","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.01066","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_12","alias_value":"VKXYI63A77UH","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_16","alias_value":"VKXYI63A77UH5FFS","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_8","alias_value":"VKXYI63A","created_at":"2026-07-05T04:37:07Z"}],"graph_snapshots":[{"event_id":"sha256:b9fd73aff0489320b3cfb317b6be1afa299310217be30f664b56f4b268e1e4c8","target":"graph","created_at":"2026-07-05T04:37:07Z","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/2207.01066/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semi-supervised learning (SSL) has been widely explored in recent years, and it is an effective way of leveraging unlabeled data to reduce the reliance on labeled data. In this work, we adjust neural processes (NPs) to the semi-supervised image classification task, resulting in a new method named NP-Match. NP-Match is suited to this task for two reasons. Firstly, NP-Match implicitly compares data points when making predictions, and as a result, the prediction of each unlabeled data point is affected by the labeled data points that are similar to it, which improves the quality of pseudo-labels.","authors_text":"Alexandros Neophytou, Daniela Massiceti, Jianfeng Wang, Thomas Lukasiewicz, Vladimir Pavlovic, Xiaolin Hu","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-03T15:24:31Z","title":"NP-Match: When Neural Processes meet Semi-Supervised Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.01066","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":"sha256:741784be77a583c9ca6fb8a75f0e4c28c34b9cb36ea65336a87787eb61cbfce0","target":"record","created_at":"2026-07-05T04:37:07Z","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":"7b1369d5ff674679f537c0736a1755b4b3ca0cd5e0251eaaac655d4dfb627ce7","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-07-03T15:24:31Z","title_canon_sha256":"e44d05a91ee152640284778b1f6e56895c921a50cf9dd5e4f4b9c7e436324b9a"},"schema_version":"1.0","source":{"id":"2207.01066","kind":"arxiv","version":1}},"canonical_sha256":"aaaf847b60ffe87e94b2161d75f4431b33d585d1d14fd0a378b1a6f2795dd678","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aaaf847b60ffe87e94b2161d75f4431b33d585d1d14fd0a378b1a6f2795dd678","first_computed_at":"2026-07-05T04:37:07.536834Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:37:07.536834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/xu7Jm7VoulJrjw9Btg5rI5iCeD26gGLZtuTEA+6AOiVKGZAIO2iEzPNMEeWZkU/pdjnM4HLMbnkusFUnZ3oAg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:37:07.537251Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.01066","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:741784be77a583c9ca6fb8a75f0e4c28c34b9cb36ea65336a87787eb61cbfce0","sha256:b9fd73aff0489320b3cfb317b6be1afa299310217be30f664b56f4b268e1e4c8"],"state_sha256":"11efaec80d16812b3ca073982a84c03659ad98e06c129234542e8aca12d6504b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u4sXy7TrBhwkQA2nEW+kqw4ObcDe9GJTsO2w2KDDQXqYpASaS22pApeyzD2lrq26yrPwEA+TxR4PlXu0cBKqDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-21T06:58:47.298715Z","bundle_sha256":"37c8b157edcf24e5b7263a686bdfaeb0dd80def9517097b52f98e96b4043873e"}}