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Paper Citation Record · LEDGER

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1705.09786.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1705.09786 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:03:38.361567Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T13:03:47.064029Z

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 5b4ceab4-6b39-48e1-8a9a-62e743bea3fd · inbound

LeMix: Unified Scheduling for LLM Training and Inference on Multi-GPU Systems cites this paper.

LeMix: Unified Scheduling for LLM Training and Inference on Multi-GPU Systems AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-06T13:03:47.160939Z

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.

source=pdf_text observed=2026-08-06T13:03:38.361567Z digest=sha256:0c72beab61650337e92e61eaaec718133c578da0a4f7332ef70cc7586247199a