Pith. sign in

Paper Citation Record · LEDGER

Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions

As of 8 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.754923Z digest=sha256:9fa2c151b8f22ae3b4947dc8b489a9f4385c9d5432d472631a3fe5fa52c0395b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.820833Z digest=sha256:c59a8ad1d5764044ed9c9bd397145c60a0702f8192068c2528e3d5a69eeb69e3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.869852Z digest=sha256:b391cb158004b4d97102ecdac579975363858e95977147215a91a527bc2c99a1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:41.959263Z digest=sha256:9302a4c22efbe95a2edaf42a4be0fe741a9a9edf593651cc073c294451d5ff26

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.039029Z digest=sha256:3ad61be8d88033fbb62780c5af96a70b7de9782127cf6657dce18fd4d812f8ee

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.114976Z digest=sha256:a37f9ee7237ec23132f2544440ab3eddfa6824e98d2e76f0be55e34e9aa02f81

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.162908Z digest=sha256:25e1731d754d92296e6f8c9e38289ec131a7a2253022d9985e81a761809abcd2

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.197782Z digest=sha256:1f43dc0b475b200163aee17e6c3e02fd9eba3091f995fafab64d83c9f49d2ed7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.257367Z digest=sha256:459091e85b1e8911170d1b90e9c7bd37cff3775cfe0b81510fb9da66b38092ca

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.487990Z digest=sha256:5e1d6899c851cc581747c8d9067d8028180df2dc6d0f407845abc2b1825af6c4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.551374Z digest=sha256:31475c83cf958f5cdc9e025578102c3fc6c6a00af0bba0e966ea834d7077d3e1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.639884Z digest=sha256:3cdaeca4d51285b47ad9baa77e6d85576d5c59212a68e64c12733306a662011c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.830754Z digest=sha256:5dc9d7b927cbf3713a6b8cf8360e75c910206505ab81f317fc5cdafd73c8ac8d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:42.928686Z digest=sha256:4302b197646b5359eef0d80967ee77ae62bf9dc9d94f9742ee672e93726952bd

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.056308Z digest=sha256:f2df3d1532e140dffbe6bf4d19e538669cfe87f5b0fedb238d6ab06dce319f96

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.187382Z digest=sha256:cf04ad21c2acb10e018065b746c0c32dd9cf8e912d9802f1d2d7ed5099c7f99c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.439778Z digest=sha256:19127ab335916b0973cc51d70253cae4febe2c12ff813441439c13eb358161f3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.523397Z digest=sha256:8b0bb8e81736dcd477060cdcf30d3b49e475c592c305949e9dbaa9942592fd08

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.606342Z digest=sha256:7dda24092c1fbfd752557604af26bb77f3741c96f19257b2b77ddaa699716245

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.690105Z digest=sha256:da8696adf5c33a79a027f3b65ab3bf7f5e0a053c7dacfb24ed620a6d3d1ba676

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.774666Z digest=sha256:346467354e7dbca5f8194734f057699f0a25d1daed9f498828d146b413eca420

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.851650Z digest=sha256:f1cf9ac77d36c492ab25693833bc07ec4a0b241fd7f10935be4792c9c71e1fa6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:43.945641Z digest=sha256:d8a8008b42de0e9ff7caf2d8c65f094ca084e1f391586c56ddab69218e70ae96

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T20:43:44.255856Z digest=sha256:d789cdbce49e75d06d7d87831426d3233d9cc861b7fa0aa7e71a21bb84f3173a

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=sha256:5ffe8e01a8afdd128262c731aab5d437a5bbff1a564736122dbb7ba53fc4d1d8

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-29T10:00:07.383219Z digest=sha256:8d06c03e727aecc4549c304d5ce55df50f051fcdb586aa150bfe37248b5b91e1