{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BAKCGOM6VCE4XBHCRDQRRNGJC3","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":"c9b86985b3e7a5aaacb87c31214db36e1eb45f78bf49a3b5c60e494a51d76485","cross_cats_sorted":["cs.AI","cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-22T23:57:11Z","title_canon_sha256":"74b95e9b8859ad50706c1b06f5f80f46c84be5b97345caf2a5fd5277fd49b9d8"},"schema_version":"1.0","source":{"id":"2507.21138","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21138","created_at":"2026-07-05T11:44:32Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21138v1","created_at":"2026-07-05T11:44:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21138","created_at":"2026-07-05T11:44:32Z"},{"alias_kind":"pith_short_12","alias_value":"BAKCGOM6VCE4","created_at":"2026-07-05T11:44:32Z"},{"alias_kind":"pith_short_16","alias_value":"BAKCGOM6VCE4XBHC","created_at":"2026-07-05T11:44:32Z"},{"alias_kind":"pith_short_8","alias_value":"BAKCGOM6","created_at":"2026-07-05T11:44:32Z"}],"graph_snapshots":[{"event_id":"sha256:3643894d7eb164b8b39eb1b23061348c93ef23bf98cdd7f1d5fc0721db0d8b22","target":"graph","created_at":"2026-07-05T11:44:32Z","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/2507.21138/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce Inworld TTS-1, a set of two Transformer-based autoregressive text-to-speech (TTS) models. Our largest model, TTS-1-Max, has 8.8B parameters and is designed for utmost quality and expressiveness in demanding applications. TTS-1 is our most efficient model, with 1.6B parameters, built for real-time speech synthesis and on-device use cases. By scaling train-time compute and applying a sequential process of pre-training, fine-tuning, and RL-alignment of the speech-language model (SpeechLM) component, both models achieve state-of-the-art performance on a variety of benchmarks, demonstr","authors_text":"Andreas Assad Kottner, Anna Chalova, Cheryl Fichter, Dmytro Semernia, Evgenii Shingarev, Feifan Fan, Florin Radu, Ian Lee, Igor Poletaev, Jasmine Mai, Jean Wang, Jimmy Du, Joseph Coombes, Kylan Gibbs, Louis Fischer, Michael Ermolenko, Mikhail Mamontov, Nikki Cope, Nurullah Morshed, Oleg Atamanenko, Oliver Louie, Pavel Filimonov, Pavel Karpik, Peter Skirko, Phillip Dang, Rinat Takhautdinov, Robert Villahermosa, Suri Mao, Valeria Gusarova, Vikram Sivaraja, Yufei Feng, Zhifeng Deng","cross_cats":["cs.AI","cs.LG","cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-22T23:57:11Z","title":"TTS-1 Technical Report"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21138","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:e4b15f8c4c79dba8c5b9071023209faf4a660a5ac8a166cebb69acafe3565137","target":"record","created_at":"2026-07-05T11:44:32Z","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":"c9b86985b3e7a5aaacb87c31214db36e1eb45f78bf49a3b5c60e494a51d76485","cross_cats_sorted":["cs.AI","cs.LG","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-07-22T23:57:11Z","title_canon_sha256":"74b95e9b8859ad50706c1b06f5f80f46c84be5b97345caf2a5fd5277fd49b9d8"},"schema_version":"1.0","source":{"id":"2507.21138","kind":"arxiv","version":1}},"canonical_sha256":"081423399ea889cb84e288e118b4c916c24597a0144eccdb75ed6a36bc17f29c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"081423399ea889cb84e288e118b4c916c24597a0144eccdb75ed6a36bc17f29c","first_computed_at":"2026-07-05T11:44:32.031149Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:44:32.031149Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ehasHVkHhufTMz2LkQSqAQR1D+s0PTTwDJcwUxTBsUu5pazZrf51ImI7ScxV4IVxLgdsyafexrLMbFVJqNfiCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:44:32.031647Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.21138","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4b15f8c4c79dba8c5b9071023209faf4a660a5ac8a166cebb69acafe3565137","sha256:3643894d7eb164b8b39eb1b23061348c93ef23bf98cdd7f1d5fc0721db0d8b22"],"state_sha256":"e465a0aaa9cbee9ceae2b8c93a35d5af38a37d23697496d9b1e2534261d6ef48"}