{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:OLTA3J4ZYSUDDHZERWT2PKIOKA","short_pith_number":"pith:OLTA3J4Z","canonical_record":{"source":{"id":"2203.01693","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-03T12:59:00Z","cross_cats_sorted":[],"title_canon_sha256":"218e54130e5b00c6176e1f81a5839d06387fe01d77c6e6f50faabc0318613aa7","abstract_canon_sha256":"f5eeca0a5f2262b400d1317f80297f5afb173c6d656dabcd34bb85adda7dd427"},"schema_version":"1.0"},"canonical_sha256":"72e60da799c4a8319f248da7a7a90e50073bbec7a8c597e6aa426b713f99902a","source":{"kind":"arxiv","id":"2203.01693","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01693","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01693v4","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01693","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_12","alias_value":"OLTA3J4ZYSUD","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_16","alias_value":"OLTA3J4ZYSUDDHZE","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_8","alias_value":"OLTA3J4Z","created_at":"2026-07-05T06:12:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:OLTA3J4ZYSUDDHZERWT2PKIOKA","target":"record","payload":{"canonical_record":{"source":{"id":"2203.01693","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-03T12:59:00Z","cross_cats_sorted":[],"title_canon_sha256":"218e54130e5b00c6176e1f81a5839d06387fe01d77c6e6f50faabc0318613aa7","abstract_canon_sha256":"f5eeca0a5f2262b400d1317f80297f5afb173c6d656dabcd34bb85adda7dd427"},"schema_version":"1.0"},"canonical_sha256":"72e60da799c4a8319f248da7a7a90e50073bbec7a8c597e6aa426b713f99902a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:12:31.398636Z","signature_b64":"Y4DezeEjMY4bQ+rkbSA8MvTQOK6CQYJYSOFycEVZHjWXN9RAdCr7yvYo5+tOOTJru31mqPOkj+u+oG+VEq9QBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72e60da799c4a8319f248da7a7a90e50073bbec7a8c597e6aa426b713f99902a","last_reissued_at":"2026-07-05T06:12:31.398122Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:12:31.398122Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.01693","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:12:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xy9T1F4T7p76TgFhtDoERPHk4pQXrfPWDYapT++ZruZDqAgZW6IOdp76Q+COB/sgsfs/JZHcvFdi7Cz61WJxBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:18:03.329305Z"},"content_sha256":"cbdde7c58c818d6064847cb238b4591cb3950c3a3297d68175b83e2a06ced9e1","schema_version":"1.0","event_id":"sha256:cbdde7c58c818d6064847cb238b4591cb3950c3a3297d68175b83e2a06ced9e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:OLTA3J4ZYSUDDHZERWT2PKIOKA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Neural Set Functions Under the Optimal Subset Oracle","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Peilin Zhao, Qinliang su, Tingyang Xu, Yatao Bian, Yingzhen Li, Zijing Ou","submitted_at":"2022-03-03T12:59:00Z","abstract_excerpt":"Learning neural set functions becomes increasingly more important in many applications like product recommendation and compound selection in AI-aided drug discovery. The majority of existing works study methodologies of set function learning under the function value oracle, which, however, requires expensive supervision signals. This renders it impractical for applications with only weak supervisions under the Optimal Subset (OS) oracle, the study of which is surprisingly overlooked. In this work, we present a principled yet practical maximum likelihood learning framework, termed as EquiVSet, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01693","kind":"arxiv","version":4},"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/2203.01693/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":"2026-07-05T06:12:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GyvlI4HWEsYvElRnbbXNK1GdBV/KuurpAzGqkXCn5tWNmaMhAgOqCRJ71XaQmfRtILpPOokMkxlkd9qIzkcBDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T14:18:03.329701Z"},"content_sha256":"b811f1204edc11200650e3097be0683dbdceb4b045faf6af58be6d1ec9bbf710","schema_version":"1.0","event_id":"sha256:b811f1204edc11200650e3097be0683dbdceb4b045faf6af58be6d1ec9bbf710"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/bundle.json","state_url":"https://pith.science/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/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":"2026-07-07T14:18:03Z","links":{"resolver":"https://pith.science/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA","bundle":"https://pith.science/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/bundle.json","state":"https://pith.science/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OLTA3J4ZYSUDDHZERWT2PKIOKA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:OLTA3J4ZYSUDDHZERWT2PKIOKA","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":"f5eeca0a5f2262b400d1317f80297f5afb173c6d656dabcd34bb85adda7dd427","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-03T12:59:00Z","title_canon_sha256":"218e54130e5b00c6176e1f81a5839d06387fe01d77c6e6f50faabc0318613aa7"},"schema_version":"1.0","source":{"id":"2203.01693","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01693","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01693v4","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01693","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_12","alias_value":"OLTA3J4ZYSUD","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_16","alias_value":"OLTA3J4ZYSUDDHZE","created_at":"2026-07-05T06:12:31Z"},{"alias_kind":"pith_short_8","alias_value":"OLTA3J4Z","created_at":"2026-07-05T06:12:31Z"}],"graph_snapshots":[{"event_id":"sha256:b811f1204edc11200650e3097be0683dbdceb4b045faf6af58be6d1ec9bbf710","target":"graph","created_at":"2026-07-05T06:12:31Z","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/2203.01693/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning neural set functions becomes increasingly more important in many applications like product recommendation and compound selection in AI-aided drug discovery. The majority of existing works study methodologies of set function learning under the function value oracle, which, however, requires expensive supervision signals. This renders it impractical for applications with only weak supervisions under the Optimal Subset (OS) oracle, the study of which is surprisingly overlooked. In this work, we present a principled yet practical maximum likelihood learning framework, termed as EquiVSet, ","authors_text":"Peilin Zhao, Qinliang su, Tingyang Xu, Yatao Bian, Yingzhen Li, Zijing Ou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-03T12:59:00Z","title":"Learning Neural Set Functions Under the Optimal Subset Oracle"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01693","kind":"arxiv","version":4},"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:cbdde7c58c818d6064847cb238b4591cb3950c3a3297d68175b83e2a06ced9e1","target":"record","created_at":"2026-07-05T06:12:31Z","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":"f5eeca0a5f2262b400d1317f80297f5afb173c6d656dabcd34bb85adda7dd427","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-03T12:59:00Z","title_canon_sha256":"218e54130e5b00c6176e1f81a5839d06387fe01d77c6e6f50faabc0318613aa7"},"schema_version":"1.0","source":{"id":"2203.01693","kind":"arxiv","version":4}},"canonical_sha256":"72e60da799c4a8319f248da7a7a90e50073bbec7a8c597e6aa426b713f99902a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"72e60da799c4a8319f248da7a7a90e50073bbec7a8c597e6aa426b713f99902a","first_computed_at":"2026-07-05T06:12:31.398122Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:12:31.398122Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y4DezeEjMY4bQ+rkbSA8MvTQOK6CQYJYSOFycEVZHjWXN9RAdCr7yvYo5+tOOTJru31mqPOkj+u+oG+VEq9QBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:12:31.398636Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.01693","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cbdde7c58c818d6064847cb238b4591cb3950c3a3297d68175b83e2a06ced9e1","sha256:b811f1204edc11200650e3097be0683dbdceb4b045faf6af58be6d1ec9bbf710"],"state_sha256":"751b7d96a1a43d6690fe61ba3b235771638a190ff2980ddec29b13441643acfa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6qkQMB4WEu3A8cYGoooNpJpfwq6iMqOxWrDRkuA30nVC2lNtrcVDVinNKcgqnLuSM768Q7V1Df67JZvXYZXOBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T14:18:03.331719Z","bundle_sha256":"828f41e1211d32b69ce696c5892ecbefd102b9fdeb23feaae04ee93a69cf53d6"}}