Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1904.02619.
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 2026-08-11T23:57:57.085182Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T12:28:57.923182Z
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 215aa1ba-2c30-4b7b-b84b-352a5bd9a1ac · inbound
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation cites this paper.
emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:57:57.085182Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c554dafa-66c6-464a-bd1c-500b282021a7 · inbound
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions cites this paper.
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:26:51.219809Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96510a01-169f-4171-a80f-73aba3010a66 · inbound
Scaling and Distilling Transformer Models for sEMG cites this paper.
Scaling and Distilling Transformer Models for sEMG Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T12:28:57.928951Z
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.