{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:XGI3FCC4N5V4JXF3DIGMOSYUKW","short_pith_number":"pith:XGI3FCC4","canonical_record":{"source":{"id":"1809.06260","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-17T14:45:21Z","cross_cats_sorted":[],"title_canon_sha256":"105785d485b77f033d8982b3a1e9b9d0604a275e3bd4cd6ffd68d6c57e3ac292","abstract_canon_sha256":"dfd8b637c6c33701c159d8e31df915a60e449033a6b1ccfc7647e689795159bb"},"schema_version":"1.0"},"canonical_sha256":"b991b2885c6f6bc4dcbb1a0cc74b1455831af9a736d5fc2355317cedbf9ec180","source":{"kind":"arxiv","id":"1809.06260","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06260","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06260v1","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06260","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"pith_short_12","alias_value":"XGI3FCC4N5V4","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"XGI3FCC4N5V4JXF3","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"XGI3FCC4","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:XGI3FCC4N5V4JXF3DIGMOSYUKW","target":"record","payload":{"canonical_record":{"source":{"id":"1809.06260","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-17T14:45:21Z","cross_cats_sorted":[],"title_canon_sha256":"105785d485b77f033d8982b3a1e9b9d0604a275e3bd4cd6ffd68d6c57e3ac292","abstract_canon_sha256":"dfd8b637c6c33701c159d8e31df915a60e449033a6b1ccfc7647e689795159bb"},"schema_version":"1.0"},"canonical_sha256":"b991b2885c6f6bc4dcbb1a0cc74b1455831af9a736d5fc2355317cedbf9ec180","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:35.162332Z","signature_b64":"IJEvFKAWLSQdIhnbKTI9YZCLC8br6sgh1iqwYs+YRYAXKA4ZKOLMVgfMdiqY8wDFotEsBGqY1vpzyuhr7Q/ODQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b991b2885c6f6bc4dcbb1a0cc74b1455831af9a736d5fc2355317cedbf9ec180","last_reissued_at":"2026-05-18T00:05:35.161804Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:35.161804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.06260","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":"2026-05-18T00:05:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0+V352moOSbRjS97YSmT598TLDALUAsBRwpDMTyX7tDwYMOW5uDxsvPv4yLoFMVEVe8K4ObVjvAsfelqCMNTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T13:55:45.087837Z"},"content_sha256":"efca958e147f74e9a1d0da3cbcf36d6671c18787b6a4ca32458273b64cdae03e","schema_version":"1.0","event_id":"sha256:efca958e147f74e9a1d0da3cbcf36d6671c18787b6a4ca32458273b64cdae03e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:XGI3FCC4N5V4JXF3DIGMOSYUKW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Heng Li, Jun Feng, Minlie Huang, Shichen Liu, Wenwu Ou, Xiaoyan Zhu, Zhirong Wang","submitted_at":"2018-09-17T14:45:21Z","abstract_excerpt":"Ranking is a fundamental and widely studied problem in scenarios such as search, advertising, and recommendation. However, joint optimization for multi-scenario ranking, which aims to improve the overall performance of several ranking strategies in different scenarios, is rather untouched. Separately optimizing each individual strategy has two limitations. The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance. The second limitation is the inability o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06260","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":"2026-05-18T00:05:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1U/sFztRtjxTj2P952/EjfOBwqio2U+5xzy/Sv0y3FhH7IGJ0Dnn+q5NK4RdkAinv3QfvVCHdc6qTIC2DKpyBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T13:55:45.088500Z"},"content_sha256":"0468bb1647026054cf190eda37213cc422be73905a153c867fae1f1f537e4aec","schema_version":"1.0","event_id":"sha256:0468bb1647026054cf190eda37213cc422be73905a153c867fae1f1f537e4aec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/bundle.json","state_url":"https://pith.science/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/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":"2026-05-26T13:55:45Z","links":{"resolver":"https://pith.science/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW","bundle":"https://pith.science/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/bundle.json","state":"https://pith.science/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XGI3FCC4N5V4JXF3DIGMOSYUKW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:XGI3FCC4N5V4JXF3DIGMOSYUKW","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":"dfd8b637c6c33701c159d8e31df915a60e449033a6b1ccfc7647e689795159bb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-17T14:45:21Z","title_canon_sha256":"105785d485b77f033d8982b3a1e9b9d0604a275e3bd4cd6ffd68d6c57e3ac292"},"schema_version":"1.0","source":{"id":"1809.06260","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06260","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06260v1","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06260","created_at":"2026-05-18T00:05:35Z"},{"alias_kind":"pith_short_12","alias_value":"XGI3FCC4N5V4","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"XGI3FCC4N5V4JXF3","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"XGI3FCC4","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:0468bb1647026054cf190eda37213cc422be73905a153c867fae1f1f537e4aec","target":"graph","created_at":"2026-05-18T00:05:35Z","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":"Ranking is a fundamental and widely studied problem in scenarios such as search, advertising, and recommendation. However, joint optimization for multi-scenario ranking, which aims to improve the overall performance of several ranking strategies in different scenarios, is rather untouched. Separately optimizing each individual strategy has two limitations. The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance. The second limitation is the inability o","authors_text":"Heng Li, Jun Feng, Minlie Huang, Shichen Liu, Wenwu Ou, Xiaoyan Zhu, Zhirong Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-17T14:45:21Z","title":"Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06260","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:efca958e147f74e9a1d0da3cbcf36d6671c18787b6a4ca32458273b64cdae03e","target":"record","created_at":"2026-05-18T00:05:35Z","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":"dfd8b637c6c33701c159d8e31df915a60e449033a6b1ccfc7647e689795159bb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-17T14:45:21Z","title_canon_sha256":"105785d485b77f033d8982b3a1e9b9d0604a275e3bd4cd6ffd68d6c57e3ac292"},"schema_version":"1.0","source":{"id":"1809.06260","kind":"arxiv","version":1}},"canonical_sha256":"b991b2885c6f6bc4dcbb1a0cc74b1455831af9a736d5fc2355317cedbf9ec180","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b991b2885c6f6bc4dcbb1a0cc74b1455831af9a736d5fc2355317cedbf9ec180","first_computed_at":"2026-05-18T00:05:35.161804Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:35.161804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IJEvFKAWLSQdIhnbKTI9YZCLC8br6sgh1iqwYs+YRYAXKA4ZKOLMVgfMdiqY8wDFotEsBGqY1vpzyuhr7Q/ODQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:35.162332Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.06260","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efca958e147f74e9a1d0da3cbcf36d6671c18787b6a4ca32458273b64cdae03e","sha256:0468bb1647026054cf190eda37213cc422be73905a153c867fae1f1f537e4aec"],"state_sha256":"f6faac5b0082f7b892cdc1eba8e5d5b077ac8ad65670b039678194622e745c91"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G5gQc2gluHyUplICDjbC31D8StYagUf0fksbfsp6rn59b9TYPbqipdOECG5+m/EHXQpTgAgfQf6NMV8VZ/pVCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T13:55:45.091877Z","bundle_sha256":"4ca09602205430b0e21a9cacf10f2bd89548401146318cc14fa9b6502849b7e4"}}