{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:6VO7TXR2D4BCE4RIQ73RJJQXZ3","short_pith_number":"pith:6VO7TXR2","canonical_record":{"source":{"id":"2311.05884","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-11-10T05:57:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"09742d34bebcb91c662cb00db539df5beb237eb5ba8dd64964100647d3fea335","abstract_canon_sha256":"61fd09b4b474d047cf37640d0eba175d988374127bd83aeb4c4c991fa47712e3"},"schema_version":"1.0"},"canonical_sha256":"f55df9de3a1f0222722887f714a617ced6de6655dec2b45c14b7d69a3a2e5cf6","source":{"kind":"arxiv","id":"2311.05884","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.05884","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"arxiv_version","alias_value":"2311.05884v1","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.05884","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_12","alias_value":"6VO7TXR2D4BC","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_16","alias_value":"6VO7TXR2D4BCE4RI","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_8","alias_value":"6VO7TXR2","created_at":"2026-07-05T07:11:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:6VO7TXR2D4BCE4RIQ73RJJQXZ3","target":"record","payload":{"canonical_record":{"source":{"id":"2311.05884","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-11-10T05:57:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"09742d34bebcb91c662cb00db539df5beb237eb5ba8dd64964100647d3fea335","abstract_canon_sha256":"61fd09b4b474d047cf37640d0eba175d988374127bd83aeb4c4c991fa47712e3"},"schema_version":"1.0"},"canonical_sha256":"f55df9de3a1f0222722887f714a617ced6de6655dec2b45c14b7d69a3a2e5cf6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:11:24.532116Z","signature_b64":"W1lmqwmSkH/36kBUkLPSY9Deuf+zlVf2+pn4baZE1dFYWgX/s1HtLdsGradvpSA0Fma3wGADCPRycKOsTQuxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f55df9de3a1f0222722887f714a617ced6de6655dec2b45c14b7d69a3a2e5cf6","last_reissued_at":"2026-07-05T07:11:24.531655Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:11:24.531655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.05884","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":"2026-07-05T07:11:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4zJoZaVAZo3VQzHbP22PUVwh39WXMG9+TqHiLgXSTbOg8nHe4J4cupVAdeaCRXgh7iK2g4f2tO0XKilBPPsXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:02:13.797073Z"},"content_sha256":"a2ce6084aa72b2c4311f40a96fd769d916570f639db86deffba5d449c082c12b","schema_version":"1.0","event_id":"sha256:a2ce6084aa72b2c4311f40a96fd769d916570f639db86deffba5d449c082c12b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:6VO7TXR2D4BCE4RIQ73RJJQXZ3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Ed H. Chi, Huan Gui, Ke Yin, Lichan Hong, Long Jin, Maciej Kula, Ruoxi Wang, Taibai Xu","submitted_at":"2023-11-10T05:57:57Z","abstract_excerpt":"Learning feature interaction is the critical backbone to building recommender systems. In web-scale applications, learning feature interaction is extremely challenging due to the sparse and large input feature space; meanwhile, manually crafting effective feature interactions is infeasible because of the exponential solution space. We propose to leverage a Transformer-based architecture with attention layers to automatically capture feature interactions. Transformer architectures have witnessed great success in many domains, such as natural language processing and computer vision. However, the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.05884","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/2311.05884/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":"2026-07-05T07:11:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CxbXlKCMHvnvItFVG71899TLgQi3fu6aBHmBzMh2mzOKAAZ1SUClAKW7ODUwxiR9au72wGX8Zpwp9IJbuLUxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T17:02:13.797589Z"},"content_sha256":"cc74d33129a33936edbba53a9103ab2607ac83196503b357fd7a90cca8ad6d87","schema_version":"1.0","event_id":"sha256:cc74d33129a33936edbba53a9103ab2607ac83196503b357fd7a90cca8ad6d87"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/bundle.json","state_url":"https://pith.science/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/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":"2026-08-03T17:02:13Z","links":{"resolver":"https://pith.science/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3","bundle":"https://pith.science/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/bundle.json","state":"https://pith.science/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6VO7TXR2D4BCE4RIQ73RJJQXZ3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:6VO7TXR2D4BCE4RIQ73RJJQXZ3","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":"61fd09b4b474d047cf37640d0eba175d988374127bd83aeb4c4c991fa47712e3","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-11-10T05:57:57Z","title_canon_sha256":"09742d34bebcb91c662cb00db539df5beb237eb5ba8dd64964100647d3fea335"},"schema_version":"1.0","source":{"id":"2311.05884","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.05884","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"arxiv_version","alias_value":"2311.05884v1","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.05884","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_12","alias_value":"6VO7TXR2D4BC","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_16","alias_value":"6VO7TXR2D4BCE4RI","created_at":"2026-07-05T07:11:24Z"},{"alias_kind":"pith_short_8","alias_value":"6VO7TXR2","created_at":"2026-07-05T07:11:24Z"}],"graph_snapshots":[{"event_id":"sha256:cc74d33129a33936edbba53a9103ab2607ac83196503b357fd7a90cca8ad6d87","target":"graph","created_at":"2026-07-05T07:11:24Z","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/2311.05884/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning feature interaction is the critical backbone to building recommender systems. In web-scale applications, learning feature interaction is extremely challenging due to the sparse and large input feature space; meanwhile, manually crafting effective feature interactions is infeasible because of the exponential solution space. We propose to leverage a Transformer-based architecture with attention layers to automatically capture feature interactions. Transformer architectures have witnessed great success in many domains, such as natural language processing and computer vision. However, the","authors_text":"Ed H. Chi, Huan Gui, Ke Yin, Lichan Hong, Long Jin, Maciej Kula, Ruoxi Wang, Taibai Xu","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-11-10T05:57:57Z","title":"Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.05884","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:a2ce6084aa72b2c4311f40a96fd769d916570f639db86deffba5d449c082c12b","target":"record","created_at":"2026-07-05T07:11:24Z","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":"61fd09b4b474d047cf37640d0eba175d988374127bd83aeb4c4c991fa47712e3","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2023-11-10T05:57:57Z","title_canon_sha256":"09742d34bebcb91c662cb00db539df5beb237eb5ba8dd64964100647d3fea335"},"schema_version":"1.0","source":{"id":"2311.05884","kind":"arxiv","version":1}},"canonical_sha256":"f55df9de3a1f0222722887f714a617ced6de6655dec2b45c14b7d69a3a2e5cf6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f55df9de3a1f0222722887f714a617ced6de6655dec2b45c14b7d69a3a2e5cf6","first_computed_at":"2026-07-05T07:11:24.531655Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:11:24.531655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W1lmqwmSkH/36kBUkLPSY9Deuf+zlVf2+pn4baZE1dFYWgX/s1HtLdsGradvpSA0Fma3wGADCPRycKOsTQuxDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:11:24.532116Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.05884","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2ce6084aa72b2c4311f40a96fd769d916570f639db86deffba5d449c082c12b","sha256:cc74d33129a33936edbba53a9103ab2607ac83196503b357fd7a90cca8ad6d87"],"state_sha256":"a2a5bb97bbf45fc3cfe902854d25e191b9335f699f7eda0c17302a12573e38f1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0KcTqeNvID2nS4J+Z9616dIJ5hlPir7VB33pxRShRKJJILRe7zb7aLBcZ4kwe8agEbYyHQqA5j8tZoMfVLs7CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T17:02:13.801287Z","bundle_sha256":"e11d9755b7e8dab167a1975eb54f31ad9d60ccdd9cd126ff93cb5c8876578350"}}