Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.17957.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T06:05:11.396269Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T23:15:07.810018Z
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 619cecbf-70e3-4e07-8894-a2bc5c49bf68 · inbound
Muyan-TTS: A Trainable Text-to-Speech Model Optimized for Podcast Scenarios with a $50K Budget cites this paper.
Muyan-TTS: A Trainable Text-to-Speech Model Optimized for Podcast Scenarios with a $50K Budget Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T06:05:11.396269Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 60758394-101e-43fd-8c43-d555c12e201d · inbound
VoiceStar: Robust Zero-Shot Autoregressive TTS with Duration Control and Extrapolation cites this paper.
VoiceStar: Robust Zero-Shot Autoregressive TTS with Duration Control and Extrapolation Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:19:52.306333Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87c4c68a-098f-455c-bce0-65a18ea890e1 · inbound
PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization cites this paper.
PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T19:16:08.558473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 988ff338-f07e-43c6-b37f-8f8a5da12ae4 · inbound
PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization cites this paper.
PairAlign: A Framework for Sequence Tokenization via Self-Alignment with Applications to Audio Tokenization Improving Robustness of LLM-based Speech Synthesis by Learning Monotonic Alignment
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T23:15:07.811625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.