{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:2J2JSSWZMS63V5VGB46HUKQG3G","short_pith_number":"pith:2J2JSSWZ","canonical_record":{"source":{"id":"1907.10235","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-24T04:47:05Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"21e7d8109c25cae5f77f0cccd2355d45effbe9dc6a8bd97d7b03faff37e63c1d","abstract_canon_sha256":"f751365922dec018f5a62769c1a116fdff0e7afc97ff7b1ae80d2e0b476371a9"},"schema_version":"1.0"},"canonical_sha256":"d274994ad964bdbaf6a60f3c7a2a06d9b540ba6d91b57bc921dbd2df21705244","source":{"kind":"arxiv","id":"1907.10235","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10235","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10235v2","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10235","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_12","alias_value":"2J2JSSWZMS63","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_16","alias_value":"2J2JSSWZMS63V5VG","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_8","alias_value":"2J2JSSWZ","created_at":"2026-07-05T00:46:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:2J2JSSWZMS63V5VGB46HUKQG3G","target":"record","payload":{"canonical_record":{"source":{"id":"1907.10235","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-24T04:47:05Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"21e7d8109c25cae5f77f0cccd2355d45effbe9dc6a8bd97d7b03faff37e63c1d","abstract_canon_sha256":"f751365922dec018f5a62769c1a116fdff0e7afc97ff7b1ae80d2e0b476371a9"},"schema_version":"1.0"},"canonical_sha256":"d274994ad964bdbaf6a60f3c7a2a06d9b540ba6d91b57bc921dbd2df21705244","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:46:31.861428Z","signature_b64":"KQTcC7rD7WvOBT5OKb5HbkHdgU/BQHQxA1mi0OSFljIYvjjljYg0r3Dl6WkTkjEiBH9GMzxqYnJwzdMphNyjCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d274994ad964bdbaf6a60f3c7a2a06d9b540ba6d91b57bc921dbd2df21705244","last_reissued_at":"2026-07-05T00:46:31.860951Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:46:31.860951Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.10235","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":"2026-07-05T00:46:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f+swiWQODBhSNlyqVony/pVj8RxNpVLnsHMEjla5xnRxC21UlrTZAftB+s7k6KIl2IJd6+RYYXp7NNixA7HhCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T12:31:34.159977Z"},"content_sha256":"caa90147b1d0c8a4236be12484f4a830708a4b23a8f22a7360c9678e11b02426","schema_version":"1.0","event_id":"sha256:caa90147b1d0c8a4236be12484f4a830708a4b23a8f22a7360c9678e11b02426"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:2J2JSSWZMS63V5VGB46HUKQG3G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Aaron Flores, Alfonso Lobos Ruiz, Junwei Pan, Yizhi Mao, Yu Sun","submitted_at":"2019-07-24T04:47:05Z","abstract_excerpt":"Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry. Unlike click prediction, conversions have different types in nature, and each type may be associated with different decisive factors. In this paper, we formulate conversion prediction as a multi-task learning problem, so that the prediction models for different types of conversions can be learned together. These models share feature representations, but have their specific parameters, providing the benefit of information-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10235","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/1907.10235/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":"2026-07-05T00:46:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PRmx/MpBzFtarfNIUxZuR6ZmqQ/4nLdqDg/zmrKYM2xQTz24+lgVyRDMVP1P9liYHo52nULiTVJNLWOQFVP/Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T12:31:34.160596Z"},"content_sha256":"062835b0bf1217ae8c563e6da13d83839c54b743c94706192af8f1d0f2aa52a0","schema_version":"1.0","event_id":"sha256:062835b0bf1217ae8c563e6da13d83839c54b743c94706192af8f1d0f2aa52a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2J2JSSWZMS63V5VGB46HUKQG3G/bundle.json","state_url":"https://pith.science/pith/2J2JSSWZMS63V5VGB46HUKQG3G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2J2JSSWZMS63V5VGB46HUKQG3G/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":"2026-08-23T12:31:34Z","links":{"resolver":"https://pith.science/pith/2J2JSSWZMS63V5VGB46HUKQG3G","bundle":"https://pith.science/pith/2J2JSSWZMS63V5VGB46HUKQG3G/bundle.json","state":"https://pith.science/pith/2J2JSSWZMS63V5VGB46HUKQG3G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2J2JSSWZMS63V5VGB46HUKQG3G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2J2JSSWZMS63V5VGB46HUKQG3G","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":"f751365922dec018f5a62769c1a116fdff0e7afc97ff7b1ae80d2e0b476371a9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-24T04:47:05Z","title_canon_sha256":"21e7d8109c25cae5f77f0cccd2355d45effbe9dc6a8bd97d7b03faff37e63c1d"},"schema_version":"1.0","source":{"id":"1907.10235","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10235","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10235v2","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10235","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_12","alias_value":"2J2JSSWZMS63","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_16","alias_value":"2J2JSSWZMS63V5VG","created_at":"2026-07-05T00:46:31Z"},{"alias_kind":"pith_short_8","alias_value":"2J2JSSWZ","created_at":"2026-07-05T00:46:31Z"}],"graph_snapshots":[{"event_id":"sha256:062835b0bf1217ae8c563e6da13d83839c54b743c94706192af8f1d0f2aa52a0","target":"graph","created_at":"2026-07-05T00:46:31Z","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/1907.10235/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conversion prediction plays an important role in online advertising since Cost-Per-Action (CPA) has become one of the primary campaign performance objectives in the industry. Unlike click prediction, conversions have different types in nature, and each type may be associated with different decisive factors. In this paper, we formulate conversion prediction as a multi-task learning problem, so that the prediction models for different types of conversions can be learned together. These models share feature representations, but have their specific parameters, providing the benefit of information-","authors_text":"Aaron Flores, Alfonso Lobos Ruiz, Junwei Pan, Yizhi Mao, Yu Sun","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-24T04:47:05Z","title":"Predicting Different Types of Conversions with Multi-Task Learning in Online Advertising"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10235","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:caa90147b1d0c8a4236be12484f4a830708a4b23a8f22a7360c9678e11b02426","target":"record","created_at":"2026-07-05T00:46:31Z","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":"f751365922dec018f5a62769c1a116fdff0e7afc97ff7b1ae80d2e0b476371a9","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-24T04:47:05Z","title_canon_sha256":"21e7d8109c25cae5f77f0cccd2355d45effbe9dc6a8bd97d7b03faff37e63c1d"},"schema_version":"1.0","source":{"id":"1907.10235","kind":"arxiv","version":2}},"canonical_sha256":"d274994ad964bdbaf6a60f3c7a2a06d9b540ba6d91b57bc921dbd2df21705244","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d274994ad964bdbaf6a60f3c7a2a06d9b540ba6d91b57bc921dbd2df21705244","first_computed_at":"2026-07-05T00:46:31.860951Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:46:31.860951Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KQTcC7rD7WvOBT5OKb5HbkHdgU/BQHQxA1mi0OSFljIYvjjljYg0r3Dl6WkTkjEiBH9GMzxqYnJwzdMphNyjCg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:46:31.861428Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.10235","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:caa90147b1d0c8a4236be12484f4a830708a4b23a8f22a7360c9678e11b02426","sha256:062835b0bf1217ae8c563e6da13d83839c54b743c94706192af8f1d0f2aa52a0"],"state_sha256":"70615c37c57ff3b8edd9d7963786c800da4d656d74aeef3b09d1c3eda1ee17fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4lFmVNIjrbvh+hVBURSA8K+8K3TSz3+gqpameYYV/YTADjaZQBNOOVBx4j6nW6DaYtVfmz/fz6OQBEx3OzYzBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T12:31:34.165606Z","bundle_sha256":"d7745482fdb8a69d502c9ee761dd32ebd0092187719b1e8b1f04ebcdfe7e5584"}}