{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BZNYFRXVQPA5HIAVCKAEPMHCCQ","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":"2259edd35ff028a900e0246aa27877fed3ea8faf4cc59c4c925c48c374d53d72","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-19T01:41:56Z","title_canon_sha256":"164ea6613d7c19f39d9696bb8dd7ca570a110309df8c0dd276752f9cf67c75da"},"schema_version":"1.0","source":{"id":"2411.12157","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.12157","created_at":"2026-07-05T09:37:16Z"},{"alias_kind":"arxiv_version","alias_value":"2411.12157v1","created_at":"2026-07-05T09:37:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.12157","created_at":"2026-07-05T09:37:16Z"},{"alias_kind":"pith_short_12","alias_value":"BZNYFRXVQPA5","created_at":"2026-07-05T09:37:16Z"},{"alias_kind":"pith_short_16","alias_value":"BZNYFRXVQPA5HIAV","created_at":"2026-07-05T09:37:16Z"},{"alias_kind":"pith_short_8","alias_value":"BZNYFRXV","created_at":"2026-07-05T09:37:16Z"}],"graph_snapshots":[{"event_id":"sha256:5ea588ea25bdb57f29df9f74ffffd128c18ae46a27ff85b15476901bea58442f","target":"graph","created_at":"2026-07-05T09:37:16Z","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/2411.12157/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This research introduces a novel text generation model that combines BERT's semantic interpretation strengths with GPT-4's generative capabilities, establishing a high standard in generating coherent, contextually accurate language. Through the combined architecture, the model enhances semantic depth and maintains smooth, human-like text flow, overcoming limitations seen in prior models. Experimental benchmarks reveal that BERT-GPT-4 surpasses traditional models, including GPT-3, T5, BART, Transformer-XL, and CTRL, in key metrics like Perplexity and BLEU, showcasing its superior natural langua","authors_text":"Chihang Wang, Hongye Zheng, Jiajing Chen, Shuo Wang, Zhenhong Zhang, Zhen Qi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-19T01:41:56Z","title":"A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.12157","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":"sha256:1e068854374ca73623b2c9b25c66bcc7de9282545d8f717af1296a227598e61a","target":"record","created_at":"2026-07-05T09:37:16Z","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":"2259edd35ff028a900e0246aa27877fed3ea8faf4cc59c4c925c48c374d53d72","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-19T01:41:56Z","title_canon_sha256":"164ea6613d7c19f39d9696bb8dd7ca570a110309df8c0dd276752f9cf67c75da"},"schema_version":"1.0","source":{"id":"2411.12157","kind":"arxiv","version":1}},"canonical_sha256":"0e5b82c6f583c1d3a015128047b0e21421724a22351357f8ca9bd624c6f369ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e5b82c6f583c1d3a015128047b0e21421724a22351357f8ca9bd624c6f369ce","first_computed_at":"2026-07-05T09:37:16.897685Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:37:16.897685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K0I1E/XE6dbrowXpgNxBxxgQihkr5SKj9P8Mm38FnJnvN783ITUhYsdPrV46vamm+uJk6WMqLFUNk+7+csbnBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:37:16.898088Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.12157","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1e068854374ca73623b2c9b25c66bcc7de9282545d8f717af1296a227598e61a","sha256:5ea588ea25bdb57f29df9f74ffffd128c18ae46a27ff85b15476901bea58442f"],"state_sha256":"8cfe918dfd5597acdedd6822f02a611c3b7db4fd387a3ed390d5700c78f74faa"}