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Paper Citation Record · LEDGER

Knowledge Adaptation for Efficient Semantic Segmentation

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1903.04688.

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

pith.paper-citation-record.v1
1903.04688 v1

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 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:07:19.384002Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T14:07:19.471962Z

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 b72199ad-b861-4f59-8180-876cc641cc33 · inbound

Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations cites this paper.

Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations Knowledge Adaptation for Efficient Semantic Segmentation

Reference 67

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:07:19.476310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-14T14:07:19.384002Z digest=sha256:d306d4a3240db82de24054ab51baa74b3d5cb3119c4c921e0b53025a755b6804