Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
As of 28 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2505.04519.
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 2026-07-28T06:31:03.373048+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-25T04:33:25.028283Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T04:35:20.955614Z
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 d5261ea6-e128-4abd-9d2c-0c1430b02128 · inbound
Accelerating MoE with Dynamic In-Switch Computing on Multi-GPUs cites this paper.
Accelerating MoE with Dynamic In-Switch Computing on Multi-GPUs Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:36:17.238231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-28T06:31:03.373048+00:00.
Observation d70dfcac-ca69-476f-8926-05720f1d8ea5 · inbound
MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems cites this paper.
MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:46:20.566120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-28T06:31:03.373048+00:00.
Observation 3bb9c390-7dee-40a2-991c-7c9e03ba1aab · inbound
Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing cites this paper.
Near-Policy: Accelerating On-Policy Distillation via Asynchronous Generation and Selective Packing Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:41:11.017629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-28T06:31:03.373048+00:00.
Observation 35730974-296d-460b-b102-2a821925f719 · inbound
Hierarchical Mixture-of-Experts with Two-Stage Optimization cites this paper.
Hierarchical Mixture-of-Experts with Two-Stage Optimization Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T07:46:26.787283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-28T06:31:03.373048+00:00.
Observation b45019b8-f3e0-4bb0-bc03-b5a0b2d981b9 · inbound
Complete-muE: Optimal Hyperparameter Transfer and Scaling for MoE Models cites this paper.
Complete-muE: Optimal Hyperparameter Transfer and Scaling for MoE Models Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:35:20.958362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-28T06:31:03.373048+00:00.