Paper Citation Record · LEDGER

A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2409.16430.

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

pith.paper-citation-record.v1
2409.16430 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:49:57.049367Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:47:28.290502Z

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 904ad98e-e3fe-4545-b078-cd3969eca1fb · inbound

Normative Evaluation of Large Language Models with Everyday Moral Dilemmas cites this paper.

Normative Evaluation of Large Language Models with Everyday Moral Dilemmas A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T00:49:57.049367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 459f8561-a889-4017-9f56-052ad65e7e06 · inbound

Towards Efficient and Effective Alignment of Large Language Models cites this paper.

Towards Efficient and Effective Alignment of Large Language Models A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 149

Resolution: unresolved; no resolver link, observed 2026-08-07T04:55:42.939261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9014d36e-5e71-499f-b0c3-d3c4dbd6ca9c · inbound

Understanding How University Guidelines Address Privacy and Security Issues of Generative AI in Academic Settings cites this paper.

Understanding How University Guidelines Address Privacy and Security Issues of Generative AI in Academic Settings A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:00.777747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aff0cdc6-48d9-4b2d-a340-f122735f9e77 · inbound

Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processing cites this paper.

Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processing A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T18:33:05.098462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3782f33-dcdc-48d6-9ac8-6bdf14f117b7 · inbound

LLMs on Trial: Evaluating Judicial Fairness for Large Language Models cites this paper.

LLMs on Trial: Evaluating Judicial Fairness for Large Language Models A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:29:44.708603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a13feb6-d4e4-40fb-a239-1414680108fb · inbound

A Close Reading Approach to Gender Narrative Biases in AI-Generated Stories cites this paper.

A Close Reading Approach to Gender Narrative Biases in AI-Generated Stories A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T20:57:56.301512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9be2abda-05eb-43fd-9968-ac1a482be668 · inbound

MLLM-as-a-Judge Exhibits Model Preference Bias cites this paper.

MLLM-as-a-Judge Exhibits Model Preference Bias A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T10:01:00.229100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 769af6c9-9620-41d3-a901-bf88dbd9536d · inbound

Why Do Large Language Models Generate Harmful Content? cites this paper.

Why Do Large Language Models Generate Harmful Content? A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:21:04.795409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2d4a488e-13d9-44e1-b18d-50ade819ad85 · inbound

First, Do No Harm (With LLMs): Mitigating Racial Bias via Agentic Workflows cites this paper.

First, Do No Harm (With LLMs): Mitigating Racial Bias via Agentic Workflows A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:21:06.147028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 78abf404-383f-49ce-a905-f1b084fa428d · inbound

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models cites this paper.

Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T00:28:23.602902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dcf8444d-582f-495d-aab3-5d3831fb09f9 · inbound

Fairness-Aware Retrieval Optimization for Retrieval-Augmented Generation cites this paper.

Fairness-Aware Retrieval Optimization for Retrieval-Augmented Generation A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T19:27:43.493846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4e1708be-b078-4d3e-af8e-f5dbaf788373 · inbound

Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning cites this paper.

Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:47:28.291844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.