Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Layered gradient accumulation and modular pipeline parallelism: fast and efficient training of large language models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2106.02679.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:38:39.821748Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T22:26:13.229257Z
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 7067a381-fa49-477c-a557-111d07697ab6 · inbound
Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters cites this paper.
Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters Layered gradient accumulation and modular pipeline parallelism: fast and efficient training of large language models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:38:39.821748Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 475ab001-acfd-43f3-877b-ae2d2fb196d6 · inbound
Beyond Imaging: Vision Transformer Digital Twin Surrogates for 3D+T Biological Tissue Dynamics cites this paper.
Beyond Imaging: Vision Transformer Digital Twin Surrogates for 3D+T Biological Tissue Dynamics Layered gradient accumulation and modular pipeline parallelism: fast and efficient training of large language models
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:49:20.566377Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a3c3595-0ed5-496b-91c7-3b195963497d · inbound
Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study cites this paper.
Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study Layered gradient accumulation and modular pipeline parallelism: fast and efficient training of large language models
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:26:13.231081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.