{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:Q42TF7TQKRX6G6MUMYKCXFRHIN","short_pith_number":"pith:Q42TF7TQ","canonical_record":{"source":{"id":"2606.00282","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-05-29T19:17:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee6e09fe990bd890fe96cf8f9dc88578b8dc7cf42034b2f6a7767ec1f08af730","abstract_canon_sha256":"836b7cc84c1343a2afc6b19f7854d9e70d0f563a8623cc9c02432b8445336ec0"},"schema_version":"1.0"},"canonical_sha256":"873532fe70546fe3799466142b96274378ad9ac88802c13c1eed8f308101f164","source":{"kind":"arxiv","id":"2606.00282","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.00282","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.00282v1","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.00282","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_12","alias_value":"Q42TF7TQKRX6","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_16","alias_value":"Q42TF7TQKRX6G6MU","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_8","alias_value":"Q42TF7TQ","created_at":"2026-06-02T01:03:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:Q42TF7TQKRX6G6MUMYKCXFRHIN","target":"record","payload":{"canonical_record":{"source":{"id":"2606.00282","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-05-29T19:17:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee6e09fe990bd890fe96cf8f9dc88578b8dc7cf42034b2f6a7767ec1f08af730","abstract_canon_sha256":"836b7cc84c1343a2afc6b19f7854d9e70d0f563a8623cc9c02432b8445336ec0"},"schema_version":"1.0"},"canonical_sha256":"873532fe70546fe3799466142b96274378ad9ac88802c13c1eed8f308101f164","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:03:50.639967Z","signature_b64":"L4TrpXLJ2ZJzj143/K8kXIOC7gLoFBT6Jitq6twBoBgcvCLRl+2lbCBziixPkwEPgUI9tv0/7B6hOI+QEe/bDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"873532fe70546fe3799466142b96274378ad9ac88802c13c1eed8f308101f164","last_reissued_at":"2026-06-02T01:03:50.639409Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:03:50.639409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.00282","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":"2026-06-02T01:03:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YpWJJSj5b7YXA8EDsm/HcyE0mICvXepNzc+yS0YDcFPYJgmrask57qzEdSxgLWbxkyyZU58Kv7QvHiC/X4UKDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T10:40:39.468480Z"},"content_sha256":"664529cd4d63bb2d375cfcf4d80753c6ac85fbe706d0b9cbad563d25c8582751","schema_version":"1.0","event_id":"sha256:664529cd4d63bb2d375cfcf4d80753c6ac85fbe706d0b9cbad563d25c8582751"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:Q42TF7TQKRX6G6MUMYKCXFRHIN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.IR","authors_text":"Erik Groving, Han Huang, Jieming Di, Ling Leng, Mengtong Hu, Min Yun, Rob Malkin, Sharath Ciddu, Shivendra Pratap Singh, Tony Wang, Xiangyu Wang, Xiaoyu Chen, Yawen He, Yi Ding, Yi-Hsuan Hsieh","submitted_at":"2026-05-29T19:17:50Z","abstract_excerpt":"Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback. Traditional approaches mitigate this via model-specific knowledge distillation from source domains to a target domain. Inspired by the transformative success of synthetic data generation in large language models (LLMs), we introduce Synthetic Cross-domain Augmentation and Learning for Recommendation (SCALR), a framework that generates synthetic user-item interaction events for a target recommendation domain by leveraging observed events from a source dom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.00282","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/2606.00282/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":"2026-06-02T01:03:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"udOqPKMwUy9Xp797Oo0QFi18XHZPiuYvW11Tuh0zs4dW8zJeMU8zP+J3VnIGzIvhdt1esELbltn9zGio/sYXBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T10:40:39.468855Z"},"content_sha256":"ea6763bec9e250cf9423da15b98e035856de0f6eb694ec71df2bf3dbbcc9fa13","schema_version":"1.0","event_id":"sha256:ea6763bec9e250cf9423da15b98e035856de0f6eb694ec71df2bf3dbbcc9fa13"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/bundle.json","state_url":"https://pith.science/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/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":"2026-06-21T10:40:39Z","links":{"resolver":"https://pith.science/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN","bundle":"https://pith.science/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/bundle.json","state":"https://pith.science/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q42TF7TQKRX6G6MUMYKCXFRHIN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Q42TF7TQKRX6G6MUMYKCXFRHIN","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":"836b7cc84c1343a2afc6b19f7854d9e70d0f563a8623cc9c02432b8445336ec0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-05-29T19:17:50Z","title_canon_sha256":"ee6e09fe990bd890fe96cf8f9dc88578b8dc7cf42034b2f6a7767ec1f08af730"},"schema_version":"1.0","source":{"id":"2606.00282","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.00282","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.00282v1","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.00282","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_12","alias_value":"Q42TF7TQKRX6","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_16","alias_value":"Q42TF7TQKRX6G6MU","created_at":"2026-06-02T01:03:50Z"},{"alias_kind":"pith_short_8","alias_value":"Q42TF7TQ","created_at":"2026-06-02T01:03:50Z"}],"graph_snapshots":[{"event_id":"sha256:ea6763bec9e250cf9423da15b98e035856de0f6eb694ec71df2bf3dbbcc9fa13","target":"graph","created_at":"2026-06-02T01:03:50Z","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/2606.00282/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback. Traditional approaches mitigate this via model-specific knowledge distillation from source domains to a target domain. Inspired by the transformative success of synthetic data generation in large language models (LLMs), we introduce Synthetic Cross-domain Augmentation and Learning for Recommendation (SCALR), a framework that generates synthetic user-item interaction events for a target recommendation domain by leveraging observed events from a source dom","authors_text":"Erik Groving, Han Huang, Jieming Di, Ling Leng, Mengtong Hu, Min Yun, Rob Malkin, Sharath Ciddu, Shivendra Pratap Singh, Tony Wang, Xiangyu Wang, Xiaoyu Chen, Yawen He, Yi Ding, Yi-Hsuan Hsieh","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-05-29T19:17:50Z","title":"Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.00282","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":"sha256:664529cd4d63bb2d375cfcf4d80753c6ac85fbe706d0b9cbad563d25c8582751","target":"record","created_at":"2026-06-02T01:03:50Z","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":"836b7cc84c1343a2afc6b19f7854d9e70d0f563a8623cc9c02432b8445336ec0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2026-05-29T19:17:50Z","title_canon_sha256":"ee6e09fe990bd890fe96cf8f9dc88578b8dc7cf42034b2f6a7767ec1f08af730"},"schema_version":"1.0","source":{"id":"2606.00282","kind":"arxiv","version":1}},"canonical_sha256":"873532fe70546fe3799466142b96274378ad9ac88802c13c1eed8f308101f164","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"873532fe70546fe3799466142b96274378ad9ac88802c13c1eed8f308101f164","first_computed_at":"2026-06-02T01:03:50.639409Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T01:03:50.639409Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L4TrpXLJ2ZJzj143/K8kXIOC7gLoFBT6Jitq6twBoBgcvCLRl+2lbCBziixPkwEPgUI9tv0/7B6hOI+QEe/bDg==","signature_status":"signed_v1","signed_at":"2026-06-02T01:03:50.639967Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.00282","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:664529cd4d63bb2d375cfcf4d80753c6ac85fbe706d0b9cbad563d25c8582751","sha256:ea6763bec9e250cf9423da15b98e035856de0f6eb694ec71df2bf3dbbcc9fa13"],"state_sha256":"8c9ccfc8f7cabb552938747160075bdba5ee2ea0bb72d2e1c00c8afd9c35e877"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XufRNtfPTday2xjB9SGaDUfSR0e2MjrDrChRs/Pzaj8TFSjjIhWnuWxDhN9WG2L2iMYVDM/cHGtjXoIKITXUBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T10:40:39.470956Z","bundle_sha256":"8cc2c41daad85cfa36e1c27c1929b22eb335421e4c0e9c99241425b6101109d6"}}