{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MXMRBQ2YQR7WOIAKALT5IXH3AM","short_pith_number":"pith:MXMRBQ2Y","canonical_record":{"source":{"id":"2502.00279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-01T02:34:12Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"509167ba7c1829137b35e8237bda604f57bb7314861d56eeb04863852c78bc72","abstract_canon_sha256":"088531bd499e622e21b72e90f40626604707ae0d3df9bcbe2ae9ee992af3c5d2"},"schema_version":"1.0"},"canonical_sha256":"65d910c358847f67200a02e7d45cfb0313c62728146881b1aa4445d4332a3d61","source":{"kind":"arxiv","id":"2502.00279","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.00279","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.00279v1","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.00279","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_12","alias_value":"MXMRBQ2YQR7W","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_16","alias_value":"MXMRBQ2YQR7WOIAK","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_8","alias_value":"MXMRBQ2Y","created_at":"2026-07-05T10:08:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MXMRBQ2YQR7WOIAKALT5IXH3AM","target":"record","payload":{"canonical_record":{"source":{"id":"2502.00279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-01T02:34:12Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"509167ba7c1829137b35e8237bda604f57bb7314861d56eeb04863852c78bc72","abstract_canon_sha256":"088531bd499e622e21b72e90f40626604707ae0d3df9bcbe2ae9ee992af3c5d2"},"schema_version":"1.0"},"canonical_sha256":"65d910c358847f67200a02e7d45cfb0313c62728146881b1aa4445d4332a3d61","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:08:31.662301Z","signature_b64":"mnpqSW45jgatZQA1+o+sM0kg/B0DflQNYYNdUfWK5tSK5cwnu0L6exjtg2w9V0+EfyeXGdHbKx2tl1FMgOf1Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65d910c358847f67200a02e7d45cfb0313c62728146881b1aa4445d4332a3d61","last_reissued_at":"2026-07-05T10:08:31.661807Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:08:31.661807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.00279","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":"2026-07-05T10:08:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I2tcuCEzgi8RJqLe1JDfpNkn2UNPQggDlnwIRgakbGB+fQxChAVefi+4CORONEnYVfcq2Jq1xdWlIRJhlgzJDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T03:08:57.273134Z"},"content_sha256":"a80e3d02b3274e52efc60f7a21e109790116a1e8c8dfb9eed4f8d0e1446b878c","schema_version":"1.0","event_id":"sha256:a80e3d02b3274e52efc60f7a21e109790116a1e8c8dfb9eed4f8d0e1446b878c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MXMRBQ2YQR7WOIAKALT5IXH3AM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving realistic semi-supervised learning with doubly robust estimation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Charles Herrmann, Khiem Pham, Ramin Zabih","submitted_at":"2025-02-01T02:34:12Z","abstract_excerpt":"A major challenge in Semi-Supervised Learning (SSL) is the limited information available about the class distribution in the unlabeled data. In many real-world applications this arises from the prevalence of long-tailed distributions, where the standard pseudo-label approach to SSL is biased towards the labeled class distribution and thus performs poorly on unlabeled data. Existing methods typically assume that the unlabeled class distribution is either known a priori, which is unrealistic in most situations, or estimate it on-the-fly using the pseudo-labels themselves. We propose to explicitl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.00279","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/2502.00279/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":"2026-07-05T10:08:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MIFAcIRwFKQUUivTQOkkSFIXMll+zSyXwZXrRE2phyf2Z3VxUVlTuIipROMJdELxWFnd5LuR7uKqKNbzOkeqBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T03:08:57.273854Z"},"content_sha256":"d9e1f44c046592f6fab9810f233ae70f51e60be3055284c2d745f97c30367b43","schema_version":"1.0","event_id":"sha256:d9e1f44c046592f6fab9810f233ae70f51e60be3055284c2d745f97c30367b43"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/bundle.json","state_url":"https://pith.science/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/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":"2026-08-10T03:08:57Z","links":{"resolver":"https://pith.science/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM","bundle":"https://pith.science/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/bundle.json","state":"https://pith.science/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MXMRBQ2YQR7WOIAKALT5IXH3AM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MXMRBQ2YQR7WOIAKALT5IXH3AM","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":"088531bd499e622e21b72e90f40626604707ae0d3df9bcbe2ae9ee992af3c5d2","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-01T02:34:12Z","title_canon_sha256":"509167ba7c1829137b35e8237bda604f57bb7314861d56eeb04863852c78bc72"},"schema_version":"1.0","source":{"id":"2502.00279","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.00279","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.00279v1","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.00279","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_12","alias_value":"MXMRBQ2YQR7W","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_16","alias_value":"MXMRBQ2YQR7WOIAK","created_at":"2026-07-05T10:08:31Z"},{"alias_kind":"pith_short_8","alias_value":"MXMRBQ2Y","created_at":"2026-07-05T10:08:31Z"}],"graph_snapshots":[{"event_id":"sha256:d9e1f44c046592f6fab9810f233ae70f51e60be3055284c2d745f97c30367b43","target":"graph","created_at":"2026-07-05T10:08:31Z","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/2502.00279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A major challenge in Semi-Supervised Learning (SSL) is the limited information available about the class distribution in the unlabeled data. In many real-world applications this arises from the prevalence of long-tailed distributions, where the standard pseudo-label approach to SSL is biased towards the labeled class distribution and thus performs poorly on unlabeled data. Existing methods typically assume that the unlabeled class distribution is either known a priori, which is unrealistic in most situations, or estimate it on-the-fly using the pseudo-labels themselves. We propose to explicitl","authors_text":"Charles Herrmann, Khiem Pham, Ramin Zabih","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-01T02:34:12Z","title":"Improving realistic semi-supervised learning with doubly robust estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.00279","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:a80e3d02b3274e52efc60f7a21e109790116a1e8c8dfb9eed4f8d0e1446b878c","target":"record","created_at":"2026-07-05T10:08:31Z","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":"088531bd499e622e21b72e90f40626604707ae0d3df9bcbe2ae9ee992af3c5d2","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-01T02:34:12Z","title_canon_sha256":"509167ba7c1829137b35e8237bda604f57bb7314861d56eeb04863852c78bc72"},"schema_version":"1.0","source":{"id":"2502.00279","kind":"arxiv","version":1}},"canonical_sha256":"65d910c358847f67200a02e7d45cfb0313c62728146881b1aa4445d4332a3d61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65d910c358847f67200a02e7d45cfb0313c62728146881b1aa4445d4332a3d61","first_computed_at":"2026-07-05T10:08:31.661807Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:08:31.661807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mnpqSW45jgatZQA1+o+sM0kg/B0DflQNYYNdUfWK5tSK5cwnu0L6exjtg2w9V0+EfyeXGdHbKx2tl1FMgOf1Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:08:31.662301Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.00279","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a80e3d02b3274e52efc60f7a21e109790116a1e8c8dfb9eed4f8d0e1446b878c","sha256:d9e1f44c046592f6fab9810f233ae70f51e60be3055284c2d745f97c30367b43"],"state_sha256":"2fbe0e47e54cd5db628613db256f84d69d2e534f9c4a4dc3beca50f681cc0de2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+UZbK0WC6nRH8qrsTglV0JI4F2iVkHkcHqUcH0VloQnKTMPp5RJgM2l0j9HRFvVebgsMxr8aQSfXBz7+iyysDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T03:08:57.280179Z","bundle_sha256":"54623511299678e025c37fc3d7c942c60648144153b96a701bc0c415d2d06298"}}