{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:TDPGRBONSPV6N356YAXTJHBS5K","short_pith_number":"pith:TDPGRBON","canonical_record":{"source":{"id":"1806.04815","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-06-13T01:45:11Z","cross_cats_sorted":[],"title_canon_sha256":"7b42e12ab27bfe4ca32ea98c5056d40a54f60d7182ee6b0f6ff22515637b6b62","abstract_canon_sha256":"cec891bcc24da61c1e5ae8f37968ab9bd674706e92588c4672363920136f19f2"},"schema_version":"1.0"},"canonical_sha256":"98de6885cd93ebe6efbec02f349c32ea8d966baec974c250b814bb861cbdf1f3","source":{"kind":"arxiv","id":"1806.04815","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04815","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04815v1","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04815","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"TDPGRBONSPV6","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"TDPGRBONSPV6N356","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"TDPGRBON","created_at":"2026-05-18T12:32:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:TDPGRBONSPV6N356YAXTJHBS5K","target":"record","payload":{"canonical_record":{"source":{"id":"1806.04815","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-06-13T01:45:11Z","cross_cats_sorted":[],"title_canon_sha256":"7b42e12ab27bfe4ca32ea98c5056d40a54f60d7182ee6b0f6ff22515637b6b62","abstract_canon_sha256":"cec891bcc24da61c1e5ae8f37968ab9bd674706e92588c4672363920136f19f2"},"schema_version":"1.0"},"canonical_sha256":"98de6885cd93ebe6efbec02f349c32ea8d966baec974c250b814bb861cbdf1f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:20.817257Z","signature_b64":"Kp0O0AzSwPN5VxH/Z0hU9pUPVQSRi5ZiBueRWNFp/l3wgnB2hHcTZnsQVh4zBoU1k5nHfWzKGEh0vjbB3KCEAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"98de6885cd93ebe6efbec02f349c32ea8d966baec974c250b814bb861cbdf1f3","last_reissued_at":"2026-05-18T00:13:20.816701Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:20.816701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.04815","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":"2026-05-18T00:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G99Jc+Bi2qKd4Hu08dDhgPsXcrG3kF7ngn5CdUMP4djS3j6bUjX0QyHFuksp0JqOO+wmwbRxOGSkzFlG+3u3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:07:41.467752Z"},"content_sha256":"a7f3dc7aa0765c675e57d079f04147354c165c8333cc065ea5a93a508b3c91ec","schema_version":"1.0","event_id":"sha256:a7f3dc7aa0765c675e57d079f04147354c165c8333cc065ea5a93a508b3c91ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:TDPGRBONSPV6N356YAXTJHBS5K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Theoretical Understanding of Weak Supervision for Information Retrieval","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Hamed Zamani, W. Bruce Croft","submitted_at":"2018-06-13T01:45:11Z","abstract_excerpt":"Neural network approaches have recently shown to be effective in several information retrieval (IR) tasks. However, neural approaches often require large volumes of training data to perform effectively, which is not always available. To mitigate the shortage of labeled data, training neural IR models with weak supervision has been recently proposed and received considerable attention in the literature. In weak supervision, an existing model automatically generates labels for a large set of unlabeled data, and a machine learning model is further trained on the generated \"weak\" data. Surprisingl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04815","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":""},"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":"2026-05-18T00:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H04Uc2uDxjaLTKOXMWtZds5yjYzTAxrahi1hQNnPtJcAtgvKnt2dxg42HoE3GmCmfyYCba7iw9s5qijFgmLmBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:07:41.468418Z"},"content_sha256":"9d2d45987c47ed958807d4b39aee7d69724dad4c755eea45090a486f478dfdeb","schema_version":"1.0","event_id":"sha256:9d2d45987c47ed958807d4b39aee7d69724dad4c755eea45090a486f478dfdeb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TDPGRBONSPV6N356YAXTJHBS5K/bundle.json","state_url":"https://pith.science/pith/TDPGRBONSPV6N356YAXTJHBS5K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TDPGRBONSPV6N356YAXTJHBS5K/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":"2026-06-11T21:07:41Z","links":{"resolver":"https://pith.science/pith/TDPGRBONSPV6N356YAXTJHBS5K","bundle":"https://pith.science/pith/TDPGRBONSPV6N356YAXTJHBS5K/bundle.json","state":"https://pith.science/pith/TDPGRBONSPV6N356YAXTJHBS5K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TDPGRBONSPV6N356YAXTJHBS5K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:TDPGRBONSPV6N356YAXTJHBS5K","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":"cec891bcc24da61c1e5ae8f37968ab9bd674706e92588c4672363920136f19f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-06-13T01:45:11Z","title_canon_sha256":"7b42e12ab27bfe4ca32ea98c5056d40a54f60d7182ee6b0f6ff22515637b6b62"},"schema_version":"1.0","source":{"id":"1806.04815","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04815","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04815v1","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04815","created_at":"2026-05-18T00:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"TDPGRBONSPV6","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"TDPGRBONSPV6N356","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"TDPGRBON","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:9d2d45987c47ed958807d4b39aee7d69724dad4c755eea45090a486f478dfdeb","target":"graph","created_at":"2026-05-18T00:13:20Z","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"},"paper":{"abstract_excerpt":"Neural network approaches have recently shown to be effective in several information retrieval (IR) tasks. However, neural approaches often require large volumes of training data to perform effectively, which is not always available. To mitigate the shortage of labeled data, training neural IR models with weak supervision has been recently proposed and received considerable attention in the literature. In weak supervision, an existing model automatically generates labels for a large set of unlabeled data, and a machine learning model is further trained on the generated \"weak\" data. Surprisingl","authors_text":"Hamed Zamani, W. Bruce Croft","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-06-13T01:45:11Z","title":"Towards Theoretical Understanding of Weak Supervision for Information Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04815","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:a7f3dc7aa0765c675e57d079f04147354c165c8333cc065ea5a93a508b3c91ec","target":"record","created_at":"2026-05-18T00:13:20Z","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":"cec891bcc24da61c1e5ae8f37968ab9bd674706e92588c4672363920136f19f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2018-06-13T01:45:11Z","title_canon_sha256":"7b42e12ab27bfe4ca32ea98c5056d40a54f60d7182ee6b0f6ff22515637b6b62"},"schema_version":"1.0","source":{"id":"1806.04815","kind":"arxiv","version":1}},"canonical_sha256":"98de6885cd93ebe6efbec02f349c32ea8d966baec974c250b814bb861cbdf1f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"98de6885cd93ebe6efbec02f349c32ea8d966baec974c250b814bb861cbdf1f3","first_computed_at":"2026-05-18T00:13:20.816701Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:20.816701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kp0O0AzSwPN5VxH/Z0hU9pUPVQSRi5ZiBueRWNFp/l3wgnB2hHcTZnsQVh4zBoU1k5nHfWzKGEh0vjbB3KCEAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:20.817257Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.04815","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a7f3dc7aa0765c675e57d079f04147354c165c8333cc065ea5a93a508b3c91ec","sha256:9d2d45987c47ed958807d4b39aee7d69724dad4c755eea45090a486f478dfdeb"],"state_sha256":"a4da5e493e38c3b75218d926ff3539cf6f823ae1dd00d23d9ec5a1ed6d2b04fe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FVEXVl/XbgcfaoGv31CgZStJtyD2GVWO5REESQyAiUy+bm6xo7VWzbxQ4M6FBQQjxFHcdpfaY9F5/fqIt/+CBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T21:07:41.472228Z","bundle_sha256":"6e9b4a35374f04baf5cf699f622179e94adeddda39a45c14e122469fe1742dff"}}