Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Experts Weights Averaging: A New General Training Scheme for Vision Transformers
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.06093.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T07:33:05.152405Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T05:21:29.947991Z
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 0ef6419d-b080-423c-a3d5-3595d6c6baf5 · inbound
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs Experts Weights Averaging: A New General Training Scheme for Vision Transformers
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:31:18.788502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e0ce55bd-4e81-4248-81a5-5902bed0a430 · inbound
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.
AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs Experts Weights Averaging: A New General Training Scheme for Vision Transformers
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:21:29.997408Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 16912c84-36d5-44bb-96f6-35527dfdbbde · inbound
Towards Privacy-Preserving Federated Prompt Tuning under Data Heterogeneity: A Subspace-Decomposed Expert Approach cites this paper.
Towards Privacy-Preserving Federated Prompt Tuning under Data Heterogeneity: A Subspace-Decomposed Expert Approach Experts Weights Averaging: A New General Training Scheme for Vision Transformers
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T07:33:05.152405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.