Paper Citation Record · LEDGER

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions

As of 10 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 2 inbound Pith citation observations for arXiv:2507.02087.

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

pith.paper-citation-record.v1
2507.02087 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:43:44.550528Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:20:40.700533Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T10:03:17.074702Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy24
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82543ff5-a87d-4be2-bf38-02f9d0332b8b · outbound

This paper cites Persistent anti-muslim bias in large language models.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Persistent anti-muslim bias in large language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:49.425434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8161cea5-df48-4a67-93ee-ded0d9f49f66 · outbound

This paper cites Categorical Data Analysis.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Categorical Data Analysis

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:49.225973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9470a22-46c2-465c-ab60-af4906293fb0 · outbound

This paper cites Claude 3.5 v2 : A research model for safe and creative reasoning.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Claude 3.5 v2 : A research model for safe and creative reasoning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.960158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4df5eff6-36ae-4263-b904-07dc54e96a11 · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pages 610--623, 2021.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pages 610--623, 2021

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.661857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 08e465ca-7076-4dc2-bda5-1b6b142749ef · outbound

This paper cites Are Emily and Greg more employable than Lakisha and Jamal ? A field experiment on labor market discrimination.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Are Emily and Greg more employable than Lakisha and Jamal ? A field experiment on labor market discrimination

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.467822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6fc886a-8599-4aeb-b86d-8ffbca916753 · outbound

This paper cites Putting fairness principles into practice: Challenges, metrics, and improvements.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Putting fairness principles into practice: Challenges, metrics, and improvements

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.273344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 77b2655a-8ffa-44f5-8d43-32204728aa9b · outbound

This paper cites Man is to computer programmer as woman is to homemaker? debiasing word embeddings.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Man is to computer programmer as woman is to homemaker? debiasing word embeddings

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.198558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a2a08067-83b9-4206-a2c1-93ad58eb792c · outbound

This paper cites Bias audit for New York City local law 144: Summary of bias audit results.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Bias audit for New York City local law 144: Summary of bias audit results

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.147410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 848a682b-956b-40b2-a3e3-622860068bdc · outbound

This paper cites Brown et al.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Brown et al

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:48.029504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a8aed1b-30e2-43bb-a64f-cad030bcdf3e · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Evaluating Large Language Models Trained on Code

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:42.352742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccb65671-1631-4731-85e5-0c6cbd9fcbd4 · outbound

This paper cites Amazon scraps secret AI recruiting tool that showed bias against women.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Amazon scraps secret AI recruiting tool that showed bias against women

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.909705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation da65ca8a-3689-4d46-9f3f-070aa62845b6 · outbound

This paper cites Gemini 1.5: Scaling up token capacity for large language models, 2024.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Gemini 1.5: Scaling up token capacity for large language models, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.803321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2c6212f4-cdb0-46ef-b727-7e7d5e591c79 · outbound

This paper cites Deepseek R1 : Retrieval‑augmented open‑weight language model.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Deepseek R1 : Retrieval‑augmented open‑weight language model

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.698025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 98a60866-9b39-40ec-a988-1c5a3aa62561 · outbound

This paper cites Auditing the Use of Language Models to Guide Hiring Decisions.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Auditing the Use of Language Models to Guide Hiring Decisions

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:42.733690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 164e2f37-7490-4662-8515-2b546676870a · outbound

This paper cites Hanley and Barbara J.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Hanley and Barbara J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.589086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a039d212-e6fd-4c91-a98a-0ba08869bfb9 · outbound

This paper cites 99\ Online: https://www.jobscan.co/blog/99-percent-fortune-500-ats/, November 2019.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions 99\ Online: https://www.jobscan.co/blog/99-percent-fortune-500-ats/, November 2019

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.489179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c903698b-96b3-4443-91af-c4246da9091f · outbound

This paper cites Documenting high-risk AI : A European regulatory perspective.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Documenting high-risk AI : A European regulatory perspective

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.388709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c77bd507-fbab-4515-abf3-9e9e50286c9e · outbound

This paper cites Obtaining confidence intervals for the risk ratio in cohort studies.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Obtaining confidence intervals for the risk ratio in cohort studies

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.254301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2b2d86e8-0460-49ad-9524-a01d06d5ddaa · outbound

This paper cites Holistic Evaluation of Language Models.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Holistic Evaluation of Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:43.336489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 864d47f2-d445-49f4-867d-144b3e493cfa · outbound

This paper cites A hiring law blazes a path for AI regulation.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions A hiring law blazes a path for AI regulation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:47.139944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 54b54446-36e9-4699-9d8b-67ad033e40b1 · outbound

This paper cites The Llama 4 herd: The beginning of a new era of natively multimodal ai innovation.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions The Llama 4 herd: The beginning of a new era of natively multimodal ai innovation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:46.988920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 22bd8410-be5f-440d-a80d-13aa70abb9b2 · outbound

This paper cites Llama 3 : Open foundation models.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Llama 3 : Open foundation models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:46.820385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9d8c7cfa-5d95-4092-84a2-8206de773a31 · outbound

This paper cites NYC local law 144: Automated employment decision tool bias audit law, 2023.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions NYC local law 144: Automated employment decision tool bias audit law, 2023

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:46.669893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a4eafbd5-ee30-4f06-a821-ae9a50cc6b9a · outbound

This paper cites GPT -4 technical report, 2023.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions GPT -4 technical report, 2023

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:46.487202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8c03594f-d4ad-44e4-ab22-f3549f6e1fe2 · outbound

This paper cites Mitigating bias in algorithmic hiring: Evaluating claims and practices.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Mitigating bias in algorithmic hiring: Evaluating claims and practices

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:46.336553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 33f5d04b-97a4-4434-9e5f-3d884d3a69c0 · outbound

This paper cites Investigating hiring bias in large language models.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Investigating hiring bias in large language models

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:45.974013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62390191-ac3c-493e-aea3-67707554b037 · outbound

This paper cites JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions JobFair: A Framework for Benchmarking Gender Hiring Bias in Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:44.034179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10b14cf2-ed64-4967-9d04-c384d86bef6b · outbound

This paper cites Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:44.111962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22a4f7c6-4264-456a-9530-3130435e7681 · outbound

This paper cites Defending against neural fake news.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Defending against neural fake news

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:43:45.194957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a1410ff5-a4f7-49b6-83bf-55b35bf54519 · outbound

This paper cites Men also like shopping: Reducing gender bias amplification using corpus-level constraints.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Men also like shopping: Reducing gender bias amplification using corpus-level constraints

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:44.361876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d66a248-7965-4b83-bf2c-7a78176ef169 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T20:43:44.550528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ccb46e17-d952-43f8-81b8-fcef2f79a9d5 · inbound

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening cites this paper.

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:20:40.700533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddcccfb8-c4f0-42ec-ae1d-58e772a884e6 · inbound

Whose Name Comes Up? III: Persona Prompting Effects in LLM-Based Scholar Recommendation cites this paper.

Whose Name Comes Up? III: Persona Prompting Effects in LLM-Based Scholar Recommendation Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T10:03:17.076129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.