{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:IBJGQUP7R7YZJIUV2DPG54Q2NQ","short_pith_number":"pith:IBJGQUP7","canonical_record":{"source":{"id":"2106.00573","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2021-05-24T03:17:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f08323c87d5e4dfbb4addcff13f278098f5d2e9fdbc0c969680135fefa6779ac","abstract_canon_sha256":"571571e88211f48479c6fdbf1e4d517c0b553fb697ad64933576e076643acd8d"},"schema_version":"1.0"},"canonical_sha256":"40526851ff8ff194a295d0de6ef21a6c1bf0279f8abfdb47961c374475850183","source":{"kind":"arxiv","id":"2106.00573","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00573","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00573v1","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00573","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_12","alias_value":"IBJGQUP7R7YZ","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_16","alias_value":"IBJGQUP7R7YZJIUV","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_8","alias_value":"IBJGQUP7","created_at":"2026-07-05T02:45:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:IBJGQUP7R7YZJIUV2DPG54Q2NQ","target":"record","payload":{"canonical_record":{"source":{"id":"2106.00573","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2021-05-24T03:17:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f08323c87d5e4dfbb4addcff13f278098f5d2e9fdbc0c969680135fefa6779ac","abstract_canon_sha256":"571571e88211f48479c6fdbf1e4d517c0b553fb697ad64933576e076643acd8d"},"schema_version":"1.0"},"canonical_sha256":"40526851ff8ff194a295d0de6ef21a6c1bf0279f8abfdb47961c374475850183","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:45:08.552082Z","signature_b64":"90v9fVE+4FdUDe2BjGpu1JddNXu+V+isyGFFfuj2gtCRtYXh6tKAjgP3YCQMPFDbaTVUHR3o0R2+ucSuTWtUCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40526851ff8ff194a295d0de6ef21a6c1bf0279f8abfdb47961c374475850183","last_reissued_at":"2026-07-05T02:45:08.551709Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:45:08.551709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.00573","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":"2026-07-05T02:45:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RXEc+a8Up7m5gi0/JKtEd/gTndJDbjpDfpDtMua5SuWOLprSmA57ONiIzoLBQjgR41VpojLJt+MTTLFlBYlZAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T17:14:33.550445Z"},"content_sha256":"e1ca10d8885628048e6959c2babd04d33c79d9896e7da34e9fe6730678cf0943","schema_version":"1.0","event_id":"sha256:e1ca10d8885628048e6959c2babd04d33c79d9896e7da34e9fe6730678cf0943"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:IBJGQUP7R7YZJIUV2DPG54Q2NQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"One4all User Representation for Recommender Systems in E-commerce","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.IR","authors_text":"Hanock Kwak, Jisu Jeong, Kyung-Min Kim, Kyuyong Shin, Minkyu Kim, Seungjae Jung, Young-Jin Park","submitted_at":"2021-05-24T03:17:05Z","abstract_excerpt":"General-purpose representation learning through large-scale pre-training has shown promising results in the various machine learning fields. For an e-commerce domain, the objective of general-purpose, i.e., one for all, representations would be efficient applications for extensive downstream tasks such as user profiling, targeting, and recommendation tasks. In this paper, we systematically compare the generalizability of two learning strategies, i.e., transfer learning through the proposed model, ShopperBERT, vs. learning from scratch. ShopperBERT learns nine pretext tasks with 79.2M parameter"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00573","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/2106.00573/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":"2026-07-05T02:45:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vKXqbP9b1uYTiwmFzHY3SLVflZFb02yyk/e1S5X0heBTZpVZiQme835S7gXNki8Q2X93YAMxeS4plSb0XGmgDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T17:14:33.551046Z"},"content_sha256":"6c2a678b5fb83f558b9ce084e7760f44d5d52a43137967d200a2cbd7d5f21806","schema_version":"1.0","event_id":"sha256:6c2a678b5fb83f558b9ce084e7760f44d5d52a43137967d200a2cbd7d5f21806"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/bundle.json","state_url":"https://pith.science/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/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":"2026-08-05T17:14:33Z","links":{"resolver":"https://pith.science/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ","bundle":"https://pith.science/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/bundle.json","state":"https://pith.science/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IBJGQUP7R7YZJIUV2DPG54Q2NQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:IBJGQUP7R7YZJIUV2DPG54Q2NQ","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":"571571e88211f48479c6fdbf1e4d517c0b553fb697ad64933576e076643acd8d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2021-05-24T03:17:05Z","title_canon_sha256":"f08323c87d5e4dfbb4addcff13f278098f5d2e9fdbc0c969680135fefa6779ac"},"schema_version":"1.0","source":{"id":"2106.00573","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.00573","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"arxiv_version","alias_value":"2106.00573v1","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.00573","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_12","alias_value":"IBJGQUP7R7YZ","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_16","alias_value":"IBJGQUP7R7YZJIUV","created_at":"2026-07-05T02:45:08Z"},{"alias_kind":"pith_short_8","alias_value":"IBJGQUP7","created_at":"2026-07-05T02:45:08Z"}],"graph_snapshots":[{"event_id":"sha256:6c2a678b5fb83f558b9ce084e7760f44d5d52a43137967d200a2cbd7d5f21806","target":"graph","created_at":"2026-07-05T02:45:08Z","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/2106.00573/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"General-purpose representation learning through large-scale pre-training has shown promising results in the various machine learning fields. For an e-commerce domain, the objective of general-purpose, i.e., one for all, representations would be efficient applications for extensive downstream tasks such as user profiling, targeting, and recommendation tasks. In this paper, we systematically compare the generalizability of two learning strategies, i.e., transfer learning through the proposed model, ShopperBERT, vs. learning from scratch. ShopperBERT learns nine pretext tasks with 79.2M parameter","authors_text":"Hanock Kwak, Jisu Jeong, Kyung-Min Kim, Kyuyong Shin, Minkyu Kim, Seungjae Jung, Young-Jin Park","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2021-05-24T03:17:05Z","title":"One4all User Representation for Recommender Systems in E-commerce"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.00573","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:e1ca10d8885628048e6959c2babd04d33c79d9896e7da34e9fe6730678cf0943","target":"record","created_at":"2026-07-05T02:45:08Z","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":"571571e88211f48479c6fdbf1e4d517c0b553fb697ad64933576e076643acd8d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2021-05-24T03:17:05Z","title_canon_sha256":"f08323c87d5e4dfbb4addcff13f278098f5d2e9fdbc0c969680135fefa6779ac"},"schema_version":"1.0","source":{"id":"2106.00573","kind":"arxiv","version":1}},"canonical_sha256":"40526851ff8ff194a295d0de6ef21a6c1bf0279f8abfdb47961c374475850183","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40526851ff8ff194a295d0de6ef21a6c1bf0279f8abfdb47961c374475850183","first_computed_at":"2026-07-05T02:45:08.551709Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:45:08.551709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"90v9fVE+4FdUDe2BjGpu1JddNXu+V+isyGFFfuj2gtCRtYXh6tKAjgP3YCQMPFDbaTVUHR3o0R2+ucSuTWtUCg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:45:08.552082Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.00573","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e1ca10d8885628048e6959c2babd04d33c79d9896e7da34e9fe6730678cf0943","sha256:6c2a678b5fb83f558b9ce084e7760f44d5d52a43137967d200a2cbd7d5f21806"],"state_sha256":"495cbfc6b2f8eca05d423d7be7abcbdad4859d477734c80a95bbb1e1efd97754"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8blsA21QUhscpKbdJxDVTPu3wLbTG2d3tJeq37kMuVb+lCcoC9/ypjvdHKogn73P+58HoDfvyEnaTbBLPRI9Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T17:14:33.555109Z","bundle_sha256":"75703ddbeb4cd2d1ccf4a4b0fc4f1fbf2c5dbd18509135756275c2270e0421ab"}}