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Paper Citation Record · LEDGER

Using LLMs for Explaining Sets of Counterfactual Examples to Final Users

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.15133.

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

pith.paper-citation-record.v1
2408.15133 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:05.031793Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T13:44:40.639824Z

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 e11bbf4e-ed03-4852-96e7-d62d26d885ae · inbound

Let's Get You Hired: A Job Seeker's Perspective on Multi-Agent Recruitment Systems for Explaining Hiring Decisions cites this paper.

Let's Get You Hired: A Job Seeker's Perspective on Multi-Agent Recruitment Systems for Explaining Hiring Decisions Using LLMs for Explaining Sets of Counterfactual Examples to Final Users

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:05.031793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:03:05.031793Z digest=sha256:e5487bbeefdc6102813af7da97fbb9d136fd98774957077dc2e83467c98a86d1

Observation 415ee06b-1e03-46ad-832e-2f63c4885f5a · inbound

Side-by-side Comparison Amplifies Dialect Bias in Language Models cites this paper.

Side-by-side Comparison Amplifies Dialect Bias in Language Models Using LLMs for Explaining Sets of Counterfactual Examples to Final Users

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-30T13:44:40.641324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T13:41:59.127845Z digest=sha256:5b0e0088325785d102530067d8512a775e632a19e662988937dbddb40a98b119