Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.03152.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:42:01.272339Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T13:21:56.578317Z
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 172f7d6a-b936-4f74-98e3-f8da32adf00f · inbound
Spatial-LLaVA: Enhancing Large Language Models with Spatial Referring Expressions for Visual Understanding cites this paper.
Spatial-LLaVA: Enhancing Large Language Models with Spatial Referring Expressions for Visual Understanding MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:42:01.272339Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e01d0042-4c78-4aab-9676-377ef9db2be8 · inbound
Leveraging LLM and Self-Supervised Training Models for Speech Recognition in Chinese Dialects: A Comparative Analysis cites this paper.
Leveraging LLM and Self-Supervised Training Models for Speech Recognition in Chinese Dialects: A Comparative Analysis MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:45:18.291161Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d65b85c7-26d4-4e4a-bc6e-80396ec46e77 · inbound
Leveraging LLM for Stuttering Speech: A Unified Architecture Bridging Recognition and Event Detection cites this paper.
Leveraging LLM for Stuttering Speech: A Unified Architecture Bridging Recognition and Event Detection MMGER: Multi-modal and Multi-granularity Generative Error Correction with LLM for Joint Accent and Speech Recognition
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T13:21:56.622044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.