{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:TUO3AKQM3ZTKSUBKZOZQLPENZJ","short_pith_number":"pith:TUO3AKQM","canonical_record":{"source":{"id":"2003.11627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-03-17T23:31:11Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"89ca3144c53d942aa61570d26d8a4f897a4a8dd4019df14e1f6965840bc1d5a6","abstract_canon_sha256":"64993f610298bfc6efbeee6b016df887f751dcfc4386d667423f6b49a14423ea"},"schema_version":"1.0"},"canonical_sha256":"9d1db02a0cde66a9502acbb305bc8dca4f0589d4998ca78dd86c879b831f3359","source":{"kind":"arxiv","id":"2003.11627","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.11627","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"arxiv_version","alias_value":"2003.11627v1","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.11627","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_12","alias_value":"TUO3AKQM3ZTK","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_16","alias_value":"TUO3AKQM3ZTKSUBK","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_8","alias_value":"TUO3AKQM","created_at":"2026-07-05T00:50:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:TUO3AKQM3ZTKSUBKZOZQLPENZJ","target":"record","payload":{"canonical_record":{"source":{"id":"2003.11627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-03-17T23:31:11Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"89ca3144c53d942aa61570d26d8a4f897a4a8dd4019df14e1f6965840bc1d5a6","abstract_canon_sha256":"64993f610298bfc6efbeee6b016df887f751dcfc4386d667423f6b49a14423ea"},"schema_version":"1.0"},"canonical_sha256":"9d1db02a0cde66a9502acbb305bc8dca4f0589d4998ca78dd86c879b831f3359","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:50:46.014396Z","signature_b64":"UtetCf1hyNkNU3IqbSABvk+wlZnbkcSwbYLfXPBlyUcHg2TVQdkvl/uoj5t4/K4jkAGNyv9ViOld2cVNuZY3Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d1db02a0cde66a9502acbb305bc8dca4f0589d4998ca78dd86c879b831f3359","last_reissued_at":"2026-07-05T00:50:46.013927Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:50:46.013927Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.11627","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":"2026-07-05T00:50:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rWwq5t8yL+pF/KZihepcN7xfkrXOUiGe6pWhZD1qB+mQQoP5EQ1+2FfNJKLEiyW/khJiuX1+64cKPUiyPcTsBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T05:58:04.257617Z"},"content_sha256":"1b0305d38d49e039c3b95062afdc86500db9f4abdfcd4786887096dffd01d8ec","schema_version":"1.0","event_id":"sha256:1b0305d38d49e039c3b95062afdc86500db9f4abdfcd4786887096dffd01d8ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:TUO3AKQM3ZTKSUBKZOZQLPENZJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Author2Vec: A Framework for Generating User Embedding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CL","authors_text":"Elena Rastorgueva, Weizhe Lin, Xiaodong Wu, Zhilin Wang","submitted_at":"2020-03-17T23:31:11Z","abstract_excerpt":"Online forums and social media platforms provide noisy but valuable data every day. In this paper, we propose a novel end-to-end neural network-based user embedding system, Author2Vec. The model incorporates sentence representations generated by BERT (Bidirectional Encoder Representations from Transformers) with a novel unsupervised pre-training objective, authorship classification, to produce better user embedding that encodes useful user-intrinsic properties. This user embedding system was pre-trained on post data of 10k Reddit users and was analyzed and evaluated on two user classification "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.11627","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/2003.11627/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":"2026-07-05T00:50:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ps7hTJVfcZwR6u8ht1JLBvYP6AzS5vgsHQ0udhPBO/xUwguP4VjQD7KQCK/jMTLG+RwDtMie/M/eH8MKRZrDDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T05:58:04.258147Z"},"content_sha256":"8b36647855999f3dc79b43f594a9aff2036383f01107c8347622a6bf64869366","schema_version":"1.0","event_id":"sha256:8b36647855999f3dc79b43f594a9aff2036383f01107c8347622a6bf64869366"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/bundle.json","state_url":"https://pith.science/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/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":"2026-08-22T05:58:04Z","links":{"resolver":"https://pith.science/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ","bundle":"https://pith.science/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/bundle.json","state":"https://pith.science/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TUO3AKQM3ZTKSUBKZOZQLPENZJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:TUO3AKQM3ZTKSUBKZOZQLPENZJ","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":"64993f610298bfc6efbeee6b016df887f751dcfc4386d667423f6b49a14423ea","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-03-17T23:31:11Z","title_canon_sha256":"89ca3144c53d942aa61570d26d8a4f897a4a8dd4019df14e1f6965840bc1d5a6"},"schema_version":"1.0","source":{"id":"2003.11627","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.11627","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"arxiv_version","alias_value":"2003.11627v1","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.11627","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_12","alias_value":"TUO3AKQM3ZTK","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_16","alias_value":"TUO3AKQM3ZTKSUBK","created_at":"2026-07-05T00:50:46Z"},{"alias_kind":"pith_short_8","alias_value":"TUO3AKQM","created_at":"2026-07-05T00:50:46Z"}],"graph_snapshots":[{"event_id":"sha256:8b36647855999f3dc79b43f594a9aff2036383f01107c8347622a6bf64869366","target":"graph","created_at":"2026-07-05T00:50:46Z","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/2003.11627/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Online forums and social media platforms provide noisy but valuable data every day. In this paper, we propose a novel end-to-end neural network-based user embedding system, Author2Vec. The model incorporates sentence representations generated by BERT (Bidirectional Encoder Representations from Transformers) with a novel unsupervised pre-training objective, authorship classification, to produce better user embedding that encodes useful user-intrinsic properties. This user embedding system was pre-trained on post data of 10k Reddit users and was analyzed and evaluated on two user classification ","authors_text":"Elena Rastorgueva, Weizhe Lin, Xiaodong Wu, Zhilin Wang","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-03-17T23:31:11Z","title":"Author2Vec: A Framework for Generating User Embedding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.11627","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":"sha256:1b0305d38d49e039c3b95062afdc86500db9f4abdfcd4786887096dffd01d8ec","target":"record","created_at":"2026-07-05T00:50:46Z","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":"64993f610298bfc6efbeee6b016df887f751dcfc4386d667423f6b49a14423ea","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-03-17T23:31:11Z","title_canon_sha256":"89ca3144c53d942aa61570d26d8a4f897a4a8dd4019df14e1f6965840bc1d5a6"},"schema_version":"1.0","source":{"id":"2003.11627","kind":"arxiv","version":1}},"canonical_sha256":"9d1db02a0cde66a9502acbb305bc8dca4f0589d4998ca78dd86c879b831f3359","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d1db02a0cde66a9502acbb305bc8dca4f0589d4998ca78dd86c879b831f3359","first_computed_at":"2026-07-05T00:50:46.013927Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:50:46.013927Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UtetCf1hyNkNU3IqbSABvk+wlZnbkcSwbYLfXPBlyUcHg2TVQdkvl/uoj5t4/K4jkAGNyv9ViOld2cVNuZY3Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T00:50:46.014396Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.11627","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b0305d38d49e039c3b95062afdc86500db9f4abdfcd4786887096dffd01d8ec","sha256:8b36647855999f3dc79b43f594a9aff2036383f01107c8347622a6bf64869366"],"state_sha256":"708e978f7497834f7507353e9eff7a1b58045d9c01d135b0ffdcdf10f9c0c65d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0c6aae7N+oZAlWGTFiXvjzvXItLddOn2My/CKAwZBH3gTpur4Khesi4TCrmIjZ6IrGtBoc6RUOYpDCYrALmGAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T05:58:04.264152Z","bundle_sha256":"8c7353690b51c6d61ab35ad7e028a884626e557d325f9ca733b9777cc01dbb27"}}