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Paper Citation Record · LEDGER

A Survey of Online Auction Mechanism Design Using Deep Learning Approaches

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.06880.

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

pith.paper-citation-record.v1
2110.06880 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:50:05.792943Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:20:37.021707Z

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 4938c8e0-4a0c-4a9c-9895-2db51580b748 · inbound

EGA-V2: An End-to-end Generative Framework for Industrial Advertising cites this paper.

EGA-V2: An End-to-end Generative Framework for Industrial Advertising A Survey of Online Auction Mechanism Design Using Deep Learning Approaches

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:50:05.792943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:50:05.792943Z digest=sha256:585fe82fad3a4afbc2b67401cab1c38b6132c0adf6612e2005721fa7e3b115f5

Observation 0b24cc60-9df9-4d99-acbb-50e7d5c35618 · inbound

NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems cites this paper.

NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems A Survey of Online Auction Mechanism Design Using Deep Learning Approaches

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:20:37.115277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:20:35.905178Z digest=sha256:d4207eda72951f68613f32c394e54709439fa05723677298a2d6f15b83ba9d03