Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2004.10694.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T10:07:33.829468Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T05:32:23.863415Z
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 2ade3b1a-f8a3-4f9d-93fc-f827966bea38 · inbound
LDA-AQU: Adaptive Query-guided Upsampling via Local Deformable Attention cites this paper.
LDA-AQU: Adaptive Query-guided Upsampling via Local Deformable Attention DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T10:07:33.829468Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebbf5a88-999f-466c-9327-c72d24567995 · inbound
Adaptive Blind Super-Resolution Network for Spatial-Specific and Spatial-Agnostic Degradations cites this paper.
Adaptive Blind Super-Resolution Network for Spatial-Specific and Spatial-Agnostic Degradations DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T05:32:23.869720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d8e2e6c9-56e8-43a2-adc9-5c2c1e43bf81 · inbound
cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs cites this paper.
cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs DyNet: Dynamic Convolution for Accelerating Convolutional Neural Networks
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:12:35.715372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.