{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5KWPH7VP4LEBN3JUNKZOZ6KPVI","short_pith_number":"pith:5KWPH7VP","canonical_record":{"source":{"id":"2607.28182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T13:19:35Z","cross_cats_sorted":[],"title_canon_sha256":"9741d5d9e92b20c731f518ea76a072a1864d7856801fba924f70e6831b781a19","abstract_canon_sha256":"bd8af108d500369a76d324e5f2a497cfc388a4fb34beae4137f46cc4b9de54e5"},"schema_version":"1.0"},"canonical_sha256":"eaacf3feafe2c816ed346ab2ecf94faa343d5f6e2b352ec170b14ace12b4db72","source":{"kind":"arxiv","id":"2607.28182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28182","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28182v1","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28182","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_12","alias_value":"5KWPH7VP4LEB","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_16","alias_value":"5KWPH7VP4LEBN3JU","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_8","alias_value":"5KWPH7VP","created_at":"2026-07-31T01:36:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5KWPH7VP4LEBN3JUNKZOZ6KPVI","target":"record","payload":{"canonical_record":{"source":{"id":"2607.28182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T13:19:35Z","cross_cats_sorted":[],"title_canon_sha256":"9741d5d9e92b20c731f518ea76a072a1864d7856801fba924f70e6831b781a19","abstract_canon_sha256":"bd8af108d500369a76d324e5f2a497cfc388a4fb34beae4137f46cc4b9de54e5"},"schema_version":"1.0"},"canonical_sha256":"eaacf3feafe2c816ed346ab2ecf94faa343d5f6e2b352ec170b14ace12b4db72","receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eaacf3feafe2c816ed346ab2ecf94faa343d5f6e2b352ec170b14ace12b4db72","last_reissued_at":"2026-07-31T01:36:24.249007Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:36:24.249007Z"},"source_kind":"arxiv","source_id":"2607.28182","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":"2026-07-31T01:36:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FDB0wxWkcJi3lS4EdY3S7g55NaYn2y4+aP9ycMPQ/CKRbI6gzaoCWB0t6z0MyRL46ztaY888mTd9b3KcsEIoCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T10:37:06.030765Z"},"content_sha256":"4bf2bfbf8134fd73b65af3672fcf7ffa0de7683072066064a73c178f0d32692a","schema_version":"1.0","event_id":"sha256:4bf2bfbf8134fd73b65af3672fcf7ffa0de7683072066064a73c178f0d32692a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5KWPH7VP4LEBN3JUNKZOZ6KPVI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-channel Uplift Policy Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bo Zheng, Changjian Liu, Chuan Yu, Jian Xu, Jungqi Jin, Tianyu Wang, Wentao Zhu, Xiaoxuan Deng, Yong Gao, Yuwei Xu","submitted_at":"2026-07-30T13:19:35Z","abstract_excerpt":"E-commerce platforms must allocate fixed marketing budgets across multiple channels to maximize business utility. However, standard predict-then-optimize (PTO) paradigms fail in this compositional space due to observational confounding and severe extrapolation. We formulate this challenge as a simplex-constrained uplift decision problem and propose ReAlloc, a fast-slow causal framework. Specifically, an agile Orthogonal Teacher extracts unbiased local gradients from short-term logs, while an Explanation-Guided Student distills them into a structured marginal field over long-term horizons. This"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28182","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/2607.28182/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":"2026-07-31T01:36:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0sxvbkPj7o2XnNrEZKImWM2pxdd2EiuODlL6Xz168QU3Bi09QnxUCLaLFB3uYOJMDSgDyYC2EKGuI7FRWVUhCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T10:37:06.031281Z"},"content_sha256":"bbe02df574984328493486f3b50f89982a2ff0045a60d5cc9bf3848c49957c5a","schema_version":"1.0","event_id":"sha256:bbe02df574984328493486f3b50f89982a2ff0045a60d5cc9bf3848c49957c5a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/bundle.json","state_url":"https://pith.science/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/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":"2026-08-03T10:37:06Z","links":{"resolver":"https://pith.science/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI","bundle":"https://pith.science/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/bundle.json","state":"https://pith.science/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5KWPH7VP4LEBN3JUNKZOZ6KPVI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5KWPH7VP4LEBN3JUNKZOZ6KPVI","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":"bd8af108d500369a76d324e5f2a497cfc388a4fb34beae4137f46cc4b9de54e5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T13:19:35Z","title_canon_sha256":"9741d5d9e92b20c731f518ea76a072a1864d7856801fba924f70e6831b781a19"},"schema_version":"1.0","source":{"id":"2607.28182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28182","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28182v1","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28182","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_12","alias_value":"5KWPH7VP4LEB","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_16","alias_value":"5KWPH7VP4LEBN3JU","created_at":"2026-07-31T01:36:24Z"},{"alias_kind":"pith_short_8","alias_value":"5KWPH7VP","created_at":"2026-07-31T01:36:24Z"}],"graph_snapshots":[{"event_id":"sha256:bbe02df574984328493486f3b50f89982a2ff0045a60d5cc9bf3848c49957c5a","target":"graph","created_at":"2026-07-31T01:36:24Z","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/2607.28182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"E-commerce platforms must allocate fixed marketing budgets across multiple channels to maximize business utility. However, standard predict-then-optimize (PTO) paradigms fail in this compositional space due to observational confounding and severe extrapolation. We formulate this challenge as a simplex-constrained uplift decision problem and propose ReAlloc, a fast-slow causal framework. Specifically, an agile Orthogonal Teacher extracts unbiased local gradients from short-term logs, while an Explanation-Guided Student distills them into a structured marginal field over long-term horizons. This","authors_text":"Bo Zheng, Changjian Liu, Chuan Yu, Jian Xu, Jungqi Jin, Tianyu Wang, Wentao Zhu, Xiaoxuan Deng, Yong Gao, Yuwei Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T13:19:35Z","title":"Multi-channel Uplift Policy Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28182","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":"sha256:4bf2bfbf8134fd73b65af3672fcf7ffa0de7683072066064a73c178f0d32692a","target":"record","created_at":"2026-07-31T01:36:24Z","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":"bd8af108d500369a76d324e5f2a497cfc388a4fb34beae4137f46cc4b9de54e5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T13:19:35Z","title_canon_sha256":"9741d5d9e92b20c731f518ea76a072a1864d7856801fba924f70e6831b781a19"},"schema_version":"1.0","source":{"id":"2607.28182","kind":"arxiv","version":1}},"canonical_sha256":"eaacf3feafe2c816ed346ab2ecf94faa343d5f6e2b352ec170b14ace12b4db72","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eaacf3feafe2c816ed346ab2ecf94faa343d5f6e2b352ec170b14ace12b4db72","first_computed_at":"2026-07-31T01:36:24.249007Z","kind":"pith_receipt","last_reissued_at":"2026-07-31T01:36:24.249007Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2607.28182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4bf2bfbf8134fd73b65af3672fcf7ffa0de7683072066064a73c178f0d32692a","sha256:bbe02df574984328493486f3b50f89982a2ff0045a60d5cc9bf3848c49957c5a"],"state_sha256":"534249136e02a756033b1f96b5ad2ac5f7bbe9d3b1222a532dfaa3e3814d66c2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5eFYcAuRmQxK5IOCcxbWkYXGDARHXZxEo7meq1SpmVg1EjP1egIwHFnbQGijG+54F+FwWzR0IhtAc14MqsgrBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T10:37:06.036258Z","bundle_sha256":"51b0e5c8b08a87484cbe33bc2976639c4f034c0e2e73583ec09ff97828d5f3b2"}}