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Paper Citation Record · LEDGER

Efficient Execution of Quantized Deep Learning Models: A Compiler Approach

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2006.10226.

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

pith.paper-citation-record.v1
2006.10226 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T00:06:40.233424Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T10:44:37.853528Z

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 df01e483-1e92-42f4-8320-e55cfcd83506 · inbound

A Comparative Study of CNN Optimization Methods for Edge AI: Exploring the Role of Early Exits cites this paper.

A Comparative Study of CNN Optimization Methods for Edge AI: Exploring the Role of Early Exits Efficient Execution of Quantized Deep Learning Models: A Compiler Approach

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:44:37.856054Z

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.

source=pdf_text observed=2026-05-10T10:40:36.879366Z digest=sha256:52d9806eb184c5c26bb9bdd055c652233da495d69a2f43b20249e6de6ca6984a

Observation e9dadcb5-091d-47b3-b82a-b29a40d3f7c5 · inbound

INT8 Quantization Makes ARM Edge Inference Dispatch-Invariant cites this paper.

INT8 Quantization Makes ARM Edge Inference Dispatch-Invariant Efficient Execution of Quantized Deep Learning Models: A Compiler Approach

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T00:06:40.233424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:06:40.233424Z digest=sha256:5babd9e7205d967ba12b45637f3740873cfde7996b0c78702cfe230901814a7a