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Paper Citation Record · LEDGER

QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.12599.

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

pith.paper-citation-record.v1
2404.12599 v2

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:23:40.789154Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T19:34:05.210441Z

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 166da92d-32bd-4e2a-ab06-c332f871e460 · inbound

DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing cites this paper.

DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:34:05.216695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T19:34:04.320049Z digest=sha256:66e9f0fc3f2855c4a6880f364de8aff1eef52da78ced9006073938c666c5370b

Observation 08b8659e-ee71-4647-a341-e4a01e65283c · inbound

TCUQ: Single-Pass Uncertainty Quantification from Temporal Consistency with Streaming Conformal Calibration for TinyML cites this paper.

TCUQ: Single-Pass Uncertainty Quantification from Temporal Consistency with Streaming Conformal Calibration for TinyML QUTE: Quantifying Uncertainty in TinyML with Early-exit-assisted ensembles for model-monitoring

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T17:23:40.789154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:23:40.789154Z digest=sha256:7e4f7dc58d51cfe83649ea1ba546aa4da9eeaecabe62ddd71e5f815902c78a95