Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
As of 3 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.08093.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-01T03:50:26.873406Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T01:17:30.982050Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation e2f60dc4-b155-4d77-ad62-d3f221336643 · inbound
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models cites this paper.
Seed-TTS: A Family of High-Quality Versatile Speech Generation Models BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T12:26:37.337799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 16b1df01-f4af-463a-8651-d4611665133e · inbound
CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models cites this paper.
CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T06:19:09.589168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 5efae641-450d-46bb-b022-57e8b05441ae · inbound
A Novel Automatic Framework for Speaker Drift Detection in Synthesized Speech cites this paper.
A Novel Automatic Framework for Speaker Drift Detection in Synthesized Speech BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:41:00.646707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 6085b80e-e5f4-4942-a4ff-fce37384abb4 · inbound
X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning cites this paper.
X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 52
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:41:16.018613Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 60e59582-95e9-4841-88cd-a75413769421 · inbound
X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning cites this paper.
X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 52
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T01:46:13.907857Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation a2492884-b458-442f-8967-03ff1d21b029 · inbound
SemaVoice: Semantic-Aware Continuous Autoregressive Speech Synthesis cites this paper.
SemaVoice: Semantic-Aware Continuous Autoregressive Speech Synthesis BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T19:02:43.574934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation e5a1bf20-4e87-4599-a4e6-88cd7a38d279 · inbound
WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling cites this paper.
WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T05:16:39.768082Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 185f221c-75e4-46f6-ad84-16083576bf82 · inbound
N\"ushuVoice: Reviving the Voice of Endangered N\"ushu with Pitch-Aware Text-to-Speech cites this paper.
N\"ushuVoice: Reviving the Voice of Endangered N\"ushu with Pitch-Aware Text-to-Speech BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 33
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T01:17:30.983342Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 67d3e437-f0e2-419f-b999-9e21f8c6829e · inbound
FlexiSLM: A Dynamic and Controllable Frame Rate Spoken Language Model cites this paper.
FlexiSLM: A Dynamic and Controllable Frame Rate Spoken Language Model BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 112
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T11:55:42.217957Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 06b38db4-bca4-471f-b398-0ccac188d768 · inbound
Is Natural Always Appropriate? Investigating Naturalness and Appropriateness Across Different Domains for TTS Evaluation cites this paper.
Is Natural Always Appropriate? Investigating Naturalness and Appropriateness Across Different Domains for TTS Evaluation BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T11:55:42.974888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.