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Paper Citation Record · LEDGER

A survey on fairness of large language models in e-commerce: progress, application, and challenge

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.13025.

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

pith.paper-citation-record.v1
2405.13025 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:46:05.433687Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:34:07.210885Z

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 adccfa2b-d470-474c-aca1-86ad6c3e8a3a · inbound

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection cites this paper.

EVADE-Bench: Multimodal Benchmark for Evaluating and Enhancing Evasive Content Detection A survey on fairness of large language models in e-commerce: progress, application, and challenge

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:05.433687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:05.433687Z digest=sha256:4fc4ac9c4df5e8bb52502c99ae958ec053a46adabc8ba3b00b2de743fb9e3e58

Observation 0917a2ee-3404-4c2a-9c9f-1f443ade1681 · inbound

MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents cites this paper.

MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents A survey on fairness of large language models in e-commerce: progress, application, and challenge

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:34:07.274471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T19:34:06.192982Z digest=sha256:43a80d226871e14af84b4e7ab26cbdbd0f7d96fd42871545d521e51630b8d76b