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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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.754923Z digest=sha256:9f08ec769495847b826009dd7e110ae862872e2bd40366daa19a0335c90c0eee

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

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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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.820833Z digest=sha256:7da7e398503f5272002a4b78f80c5466fca737dff3b24b15126683a61c38f1a0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.869852Z digest=sha256:0841e12bc70a28d62a5b6db133fac7b79bca61ff4de2a80dc13f6abcc1009ae5

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.959263Z digest=sha256:3cf479e29fc3cd9d130789270ad02ac0be9fdde31dd273bffe36d964f5a7f091

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.039029Z digest=sha256:afbbdfb7276cd6ba2f43c42a4de4fd5a6a818266dd160dd31d24b1c8ef6a0027

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.114976Z digest=sha256:09aead3e5fa8249261776f18eed428adcb88341d38ba1e497f9cbdb6e22c9d95

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.162908Z digest=sha256:9c88a6c0a98edec82d0ef4734da8a29fbd5cf3e86b616f61e58020d52b7901ca

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.197782Z digest=sha256:ff4dad747b131018c5a988ef4c8c8fd15bfea98de0331f20daf4a29e2b6ba746

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.257367Z digest=sha256:ab1c2433e57e1fb59312c5b7b83d24ef8ceefee41e8d393cb28f642769a104b1

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.

source=arxiv_source observed=2026-08-06T20:43:42.352742Z digest=sha256:145435ec09de3c49d469977365f88f4fdf858a6950f68807a6423f37b2c23316

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.487990Z digest=sha256:b0b15595e658818ef28022955077183a828c92455c1e6226be470b3049447103

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.551374Z digest=sha256:81f90adb1bc511e82fdf3d4354389f91fe936d2ab5c926908291b8bb2e321cf6

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.639884Z digest=sha256:bd305fe39a1827920c19de2158402dd3913a414c9801b0943bfb06d7f1857e8f

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.

source=arxiv_source observed=2026-08-06T20:43:42.733690Z digest=sha256:346a995fcef08eb1fe3486d083645a8ce93ccfeb5ff4edc866ee6a67e61bb262

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.830754Z digest=sha256:bf6093bffa562c6d3670b0eac6a316536b1b6dff5d3dd11a0ca597470fd00ec0

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.928686Z digest=sha256:f7921c4a7adfe95a3bc0a6febd49a724bd475fd40982e4b7e5a04e63ba27b073

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.056308Z digest=sha256:c9beefdeb24e29cdb62250e716d3b2992dbb00b12cb41a46041b5df8e6ac1afd

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.187382Z digest=sha256:84e3475f9840ae150a594f2efec275603b2aa8c6de5ff257652e404102228d28

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.

source=arxiv_source observed=2026-08-06T20:43:43.336489Z digest=sha256:4fe1c31d9a3ecc2a1806352d4a9d58e147dc303b677530834f759cb08d7e1d6c

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.439778Z digest=sha256:de86c8d0bd8d2b0a50017d4e9a7b744340b8e3a784880f0bb79f20e9bf5cf8c2

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.523397Z digest=sha256:2f7f477af0b5c3bc160273eea48b38ad0f5cb5ea8b543a63166c48c777a1f878

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.606342Z digest=sha256:ec12b2d206f0fbfd3c4a588dcf00d0fb729c967b5a2d120136dc8e31b21f39b6

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.690105Z digest=sha256:d3bdf07c1d086105f87e85477e00c4d3c05d5ea230600bd7fed7424ad3533c3c

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.774666Z digest=sha256:d53baf00c8aadb551e7f5a3ce9352271e53bc5729d78ba26f2b160a360dde2e4

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.851650Z digest=sha256:8912c00aa09b14d5be93f5445b8a1f984f4a0ad9e10c3c6ed02223fc6c340254

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.945641Z digest=sha256:91db9622925bc241e05eef4ea6c1dbdf233dfc0cdbae11090f45c19e98385ceb

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.

source=arxiv_source observed=2026-08-06T20:43:44.034179Z digest=sha256:2a130e508da61f9834cb27e6a56e2937893b8d464e676f0d7d9b1825944f4803

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.

source=arxiv_source observed=2026-08-06T20:43:44.111962Z digest=sha256:fd4ba7dc5474711972c9f82ae932cdcaa2a4f7812d2097ce330e6fdffeb2e7eb

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T20:43:44.255856Z digest=sha256:62ec6728c70590b54f11ebd34b8c0f7437bd04ab081051ed05e1f3df42902297

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.

source=arxiv_source observed=2026-08-06T20:43:44.361876Z digest=sha256:2b34ab382889e02ec75ea33a036a68290e31e951800be04df2f579808fc2187c

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.

source=arxiv_source observed=2026-08-06T20:43:44.550528Z digest=sha256:11053c14e10935e1104224996405801d093f02fa01026247a208a7382063dbc8

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.

source=pdf_text observed=2026-08-06T18:20:40.700533Z digest=sha256:a49793d54263659bd2b345dfb4dce1f81d1108cb8b59457af55c97baf3cb5c23

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T10:00:07.383219Z digest=sha256:774580a790125c35aa62e1a05fa698a5fcdc9e309e32eb661102f8743c4e3f06