Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
AMSP: Reducing Communication Overhead of ZeRO for Efficient LLM Training
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.00257.
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 2026-08-16T05:32:40.691513Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T21:42:38.395210Z
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 02bcaf6a-9e55-4078-a489-a98d61c9662c · inbound
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning cites this paper.
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning AMSP: Reducing Communication Overhead of ZeRO for Efficient LLM Training
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T21:42:38.400265Z
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.
Observation e5587562-8af1-411f-bea9-ef31fa87f0c9 · inbound
Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations cites this paper.
Hetu v2: A General and Scalable Deep Learning System with Hierarchical and Heterogeneous Single Program Multiple Data Annotations AMSP: Reducing Communication Overhead of ZeRO for Efficient LLM Training
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T05:32:40.691513Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.