{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:MQ3MFLKNILVC4KMNE3MYSZUS4P","short_pith_number":"pith:MQ3MFLKN","canonical_record":{"source":{"id":"2205.05128","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-10T19:11:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"59112adc1997add84b95083e7228ba81a7dbf66f6e8b5f7ffac84370868cbe37","abstract_canon_sha256":"e5a869f55287e4952ce28d0ccd1d8db37435a0cebb0c2d750ba48650bfeb900e"},"schema_version":"1.0"},"canonical_sha256":"6436c2ad4d42ea2e298d26d9896692e3d1326c8f9306438879b54ac87ee9a5b5","source":{"kind":"arxiv","id":"2205.05128","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.05128","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"arxiv_version","alias_value":"2205.05128v1","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.05128","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_12","alias_value":"MQ3MFLKNILVC","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_16","alias_value":"MQ3MFLKNILVC4KMN","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_8","alias_value":"MQ3MFLKN","created_at":"2026-07-05T07:10:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:MQ3MFLKNILVC4KMNE3MYSZUS4P","target":"record","payload":{"canonical_record":{"source":{"id":"2205.05128","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-10T19:11:12Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"59112adc1997add84b95083e7228ba81a7dbf66f6e8b5f7ffac84370868cbe37","abstract_canon_sha256":"e5a869f55287e4952ce28d0ccd1d8db37435a0cebb0c2d750ba48650bfeb900e"},"schema_version":"1.0"},"canonical_sha256":"6436c2ad4d42ea2e298d26d9896692e3d1326c8f9306438879b54ac87ee9a5b5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:10:45.004006Z","signature_b64":"ouBfS7UFAxeQQgxgcI85bzYUZNaHHyLqWElgn/HJ91WZAUxerCxbKGmV7ikUBg1lj4/fdap7zOqIQs2RI4lwBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6436c2ad4d42ea2e298d26d9896692e3d1326c8f9306438879b54ac87ee9a5b5","last_reissued_at":"2026-07-05T07:10:45.003629Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:10:45.003629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.05128","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":"2026-07-05T07:10:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fIk+HLiYVtzkPXmay0RFQ9u+KyxoPqa2/pLiOJwbfJhtlF30ZBKPiX/fqEa8e54iAgF4u2RgH0imzbBf04QNDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T16:00:16.576468Z"},"content_sha256":"e0783c9ba157901e58840fa4daf24dde34bfdf2cd9fca6a055da4895491eb1f3","schema_version":"1.0","event_id":"sha256:e0783c9ba157901e58840fa4daf24dde34bfdf2cd9fca6a055da4895491eb1f3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:MQ3MFLKNILVC4KMNE3MYSZUS4P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Human Language Modeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"H. Andrew Schwartz, Matthew Matero, Nikita Soni, Niranjan Balasubramanian","submitted_at":"2022-05-10T19:11:12Z","abstract_excerpt":"Natural language is generated by people, yet traditional language modeling views words or documents as if generated independently. Here, we propose human language modeling (HuLM), a hierarchical extension to the language modeling problem whereby a human-level exists to connect sequences of documents (e.g. social media messages) and capture the notion that human language is moderated by changing human states. We introduce, HaRT, a large-scale transformer model for the HuLM task, pre-trained on approximately 100,000 social media users, and demonstrate its effectiveness in terms of both language "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.05128","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/2205.05128/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":"2026-07-05T07:10:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x+UPmV4my4sfEYlEjamRA1xkCoF95AGO9GKP9NBrYyeK2078+1WGCLY59lgl12GQdaFU/6peVV9wS9y4XV9uCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T16:00:16.576845Z"},"content_sha256":"1809de8c5267bad76e964f84786429173a97764dc9d9242391a42fc5dba8527b","schema_version":"1.0","event_id":"sha256:1809de8c5267bad76e964f84786429173a97764dc9d9242391a42fc5dba8527b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/bundle.json","state_url":"https://pith.science/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/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":"2026-07-11T16:00:16Z","links":{"resolver":"https://pith.science/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P","bundle":"https://pith.science/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/bundle.json","state":"https://pith.science/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQ3MFLKNILVC4KMNE3MYSZUS4P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:MQ3MFLKNILVC4KMNE3MYSZUS4P","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":"e5a869f55287e4952ce28d0ccd1d8db37435a0cebb0c2d750ba48650bfeb900e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-10T19:11:12Z","title_canon_sha256":"59112adc1997add84b95083e7228ba81a7dbf66f6e8b5f7ffac84370868cbe37"},"schema_version":"1.0","source":{"id":"2205.05128","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.05128","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"arxiv_version","alias_value":"2205.05128v1","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.05128","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_12","alias_value":"MQ3MFLKNILVC","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_16","alias_value":"MQ3MFLKNILVC4KMN","created_at":"2026-07-05T07:10:45Z"},{"alias_kind":"pith_short_8","alias_value":"MQ3MFLKN","created_at":"2026-07-05T07:10:45Z"}],"graph_snapshots":[{"event_id":"sha256:1809de8c5267bad76e964f84786429173a97764dc9d9242391a42fc5dba8527b","target":"graph","created_at":"2026-07-05T07:10:45Z","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/2205.05128/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Natural language is generated by people, yet traditional language modeling views words or documents as if generated independently. Here, we propose human language modeling (HuLM), a hierarchical extension to the language modeling problem whereby a human-level exists to connect sequences of documents (e.g. social media messages) and capture the notion that human language is moderated by changing human states. We introduce, HaRT, a large-scale transformer model for the HuLM task, pre-trained on approximately 100,000 social media users, and demonstrate its effectiveness in terms of both language ","authors_text":"H. Andrew Schwartz, Matthew Matero, Nikita Soni, Niranjan Balasubramanian","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-10T19:11:12Z","title":"Human Language Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.05128","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:e0783c9ba157901e58840fa4daf24dde34bfdf2cd9fca6a055da4895491eb1f3","target":"record","created_at":"2026-07-05T07:10:45Z","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":"e5a869f55287e4952ce28d0ccd1d8db37435a0cebb0c2d750ba48650bfeb900e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-10T19:11:12Z","title_canon_sha256":"59112adc1997add84b95083e7228ba81a7dbf66f6e8b5f7ffac84370868cbe37"},"schema_version":"1.0","source":{"id":"2205.05128","kind":"arxiv","version":1}},"canonical_sha256":"6436c2ad4d42ea2e298d26d9896692e3d1326c8f9306438879b54ac87ee9a5b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6436c2ad4d42ea2e298d26d9896692e3d1326c8f9306438879b54ac87ee9a5b5","first_computed_at":"2026-07-05T07:10:45.003629Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:10:45.003629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ouBfS7UFAxeQQgxgcI85bzYUZNaHHyLqWElgn/HJ91WZAUxerCxbKGmV7ikUBg1lj4/fdap7zOqIQs2RI4lwBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:10:45.004006Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.05128","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0783c9ba157901e58840fa4daf24dde34bfdf2cd9fca6a055da4895491eb1f3","sha256:1809de8c5267bad76e964f84786429173a97764dc9d9242391a42fc5dba8527b"],"state_sha256":"9803bdb65aa2033d22a66393f053835aabf252dc503e2d501102d520a6159157"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xNOe9ppxNanAcXKFAI1J+9bfDn6e6h26JVSe5EuPaJQHnCHnWCvBEY6BqdsUKbAzB3N+3VAlsjj67MqZ7CAtDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T16:00:16.579299Z","bundle_sha256":"fc8e7067b0934efa9b2d48c3d051bfa1eb706a3a80cee91315ac02909029d137"}}