{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:7MRKWJJULZXBRREKOH6FJCZ4TW","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":"aa08fd72a88845c017764f797f79b3c4ae10e52f6de39c9b6adccf9f744bcfe1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-30T15:29:16Z","title_canon_sha256":"e0bbfc4bb16583bfcab4752d630dfe5c72623888ba204ff3fe87cae2ab07e8ce"},"schema_version":"1.0","source":{"id":"2010.16324","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.16324","created_at":"2026-07-05T01:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2010.16324v1","created_at":"2026-07-05T01:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.16324","created_at":"2026-07-05T01:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"7MRKWJJULZXB","created_at":"2026-07-05T01:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"7MRKWJJULZXBRREK","created_at":"2026-07-05T01:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"7MRKWJJU","created_at":"2026-07-05T01:47:52Z"}],"graph_snapshots":[{"event_id":"sha256:b989c588cc2ca6d4d26482a1094a64cdd7d41c25c82a51dda15db8abbb89e705","target":"graph","created_at":"2026-07-05T01:47:52Z","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/2010.16324/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nowadays, there exist powerful language models such as OpenAI's GPT-2 that can generate readable text and can be fine-tuned to generate text for a specific domain. Considering GPT-2, it cannot directly generate synthetic news with respect to a given topic and the output of the language model cannot be explicitly controlled. In this paper, we study the novel problem of topic-preserving synthetic news generation. We propose a novel deep reinforcement learning-based method to control the output of GPT-2 with respect to a given news topic. When generating text using GPT-2, by default, the most pro","authors_text":"Ahmadreza Mosallanezhad, Huan Liu, Kai Shu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-30T15:29:16Z","title":"Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.16324","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":"sha256:974ab02985621772da05997411d553d15255ad48c8dcb85e7a6483338933ffe5","target":"record","created_at":"2026-07-05T01:47:52Z","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":"aa08fd72a88845c017764f797f79b3c4ae10e52f6de39c9b6adccf9f744bcfe1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-30T15:29:16Z","title_canon_sha256":"e0bbfc4bb16583bfcab4752d630dfe5c72623888ba204ff3fe87cae2ab07e8ce"},"schema_version":"1.0","source":{"id":"2010.16324","kind":"arxiv","version":1}},"canonical_sha256":"fb22ab25345e6e18c48a71fc548b3c9db5cdda6a2d630960ab685ba753dc9e5e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb22ab25345e6e18c48a71fc548b3c9db5cdda6a2d630960ab685ba753dc9e5e","first_computed_at":"2026-07-05T01:47:52.356344Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:47:52.356344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VzbmxMOG8Q6KB31IMLV/REFemRnie3U1ZFh7fEHuVnxZNbkcH26Qg5yqcqtjAyR7u6r/SkewEb4/TQiyD9XNCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:47:52.356757Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.16324","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:974ab02985621772da05997411d553d15255ad48c8dcb85e7a6483338933ffe5","sha256:b989c588cc2ca6d4d26482a1094a64cdd7d41c25c82a51dda15db8abbb89e705"],"state_sha256":"e4c6daba7614f824d572213b422786cb5f7df6de4297b9e485539e513c83bb16"}