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Paper Citation Record · LEDGER

Training of Neural Networks with Uncertain Data: A Mixture of Experts Approach

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.08083.

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

pith.paper-citation-record.v1
2312.08083 v4

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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:20:53.554252Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T16:31:06.221166Z

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 6b46b6dd-dc25-4605-9827-d7fb6702e661 · inbound

EMoE: Training-Free Expert Disagreement for Uncertainty-Aware Text-to-Image Diffusion cites this paper.

EMoE: Training-Free Expert Disagreement for Uncertainty-Aware Text-to-Image Diffusion Training of Neural Networks with Uncertain Data: A Mixture of Experts Approach

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T20:20:53.554252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:20:53.554252Z digest=sha256:8f2d350938dee90cd7611e7cf5270823062bc3a293fb6391f7a7fffaabe5368b

Observation b35b0dbb-9216-472b-8662-aa0ecd13f725 · inbound

Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation cites this paper.

Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation Training of Neural Networks with Uncertain Data: A Mixture of Experts Approach

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:31:06.227676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T16:31:06.040982Z digest=sha256:b1ebd2ff7c286a98bf5dab9bb0b37ce0f9c2359ed376f8a18431256b04589725