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Paper Citation Record · LEDGER

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations

As of 13 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2501.16356.

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

pith.paper-citation-record.v1
2501.16356 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:23:36.178126Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T14:12:42.610994Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T14:13:05.842789Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e6aad687-c126-4f6f-806e-54f1c7ab48b9 · outbound

This paper cites A Survey on Evaluation of Large Language Models.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations A Survey on Evaluation of Large Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.963784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.963784Z digest=sha256:28d89d2831fdd0b3d307e81f874cae6e31b8222d9cb4e2b8e0347b20fc41447b

Observation 30ec9fa0-d8d6-409e-89df-f18a912ee98e · outbound

This paper cites DOI:10.13140/RG.2.2.27881.47207.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations DOI:10.13140/RG.2.2.27881.47207

Reference 4

Resolution
verified exact
raw_fallback, observed 2026-08-10T18:23:36.633330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:23:35.975731Z digest=sha256:11276e2c6467265bdde61f07cd6977d12f3246a75b4e32d64d3beaf6bad4dd23

Observation 322c1ea0-b07e-4255-9f6c-97c08b674fc0 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.981037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.981037Z digest=sha256:f2b675043a7c02fea080fcd16e0ffceb4627454ebec5961d0de6d63177b726c9

Observation 0fb5d55f-6970-484c-9efe-0e19fc94a745 · outbound

This paper cites Generative Agents: Interactive Simulacra of Human Behavior.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Generative Agents: Interactive Simulacra of Human Behavior

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.986804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.986804Z digest=sha256:9fe06e603f19993a562175cb899757059a909f7fb1d15fcf66a73d6a56f70691

Observation 9fdf30ff-84fb-4d39-b1d4-fe83ef9693c6 · outbound

This paper cites Is Temperature the Creativity Parameter of Large Language Models?.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Is Temperature the Creativity Parameter of Large Language Models?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.991315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.991315Z digest=sha256:c0edef1db509e7a695f41efca4c9ee8a167f64e6727bd5af2bea42e5ab24bde7

Observation d7e9adcb-a67a-45a1-af70-99eaf1f89876 · outbound

This paper cites ICML 2023 Workshop: Sampling and Optimization in Discrete Space, 4(1): 1–22.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations ICML 2023 Workshop: Sampling and Optimization in Discrete Space, 4(1): 1–22

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:23:36.686525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:23:36.011065Z digest=sha256:e7e93b88c3cdfed9a62494cf715a70332006cf1ecd19c30a13d8154a4aed42d6

Observation 74a82083-8200-4a3d-8e5e-6dbc3490c9f3 · outbound

This paper cites The Effect of Sampling Temperature on Problem Solving in Large Language Models.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations The Effect of Sampling Temperature on Problem Solving in Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:36.040931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:36.040931Z digest=sha256:cbdecc4e7a3db0917b6646464be794c325f24a1b4396a70b02132efc0f995184

Observation 0dd75173-221d-47a1-991c-8bb2a4e1c802 · outbound

This paper cites UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource Languages.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource Languages

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:23:36.407833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:23:36.067096Z digest=sha256:17dd582b011ce09d20b474e6bdf6a7edd1686ce2d45e8f9e2cb1c2361c0de612

Observation ed4fc8d7-fd6c-48f2-90a0-cda01e0dd444 · outbound

This paper cites Matching Networks for One Shot Learning.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Matching Networks for One Shot Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:36.178126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:36.178126Z digest=sha256:1945d3f533ad63a9b97edd84a730a128aa6aad7a557839f5d14bdf8e14e96785

Observation 4bda4b18-b0f8-4b05-be80-6d9ef197baaf · outbound

This paper cites Modelling Opaque Bilateral Market Dynamics in Financial Trading: Insights from a Multi-Agent Simulation Study.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Modelling Opaque Bilateral Market Dynamics in Financial Trading: Insights from a Multi-Agent Simulation Study

Reference 2017

Resolution
metadata mismatch
local_arxiv, observed 2026-08-10T18:23:36.387414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T18:23:36.107599Z digest=sha256:0c36c9ca5d609cf11cae4d7ae672ab68b3accc3065a45125eeef580ebcdd51fe

Observation 16171a9c-7568-4180-a6cd-dd255f6894cd · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.926060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.926060Z digest=sha256:fdc871ad3216cbf1989141d2f49859ee9b729e823172bb8450c606f2a608377e

Observation 6d49536c-a504-44c0-8f7b-e9cde13cdc64 · outbound

This paper cites How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips.

Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T18:23:35.969722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:23:35.969722Z digest=sha256:4f09af13519a6b540ef28a1b48a7ef0ddc70c64124db67a395fffd04146cc603

Pith citing papers

Observation fc5b9cd7-b060-4071-8bb1-435f0b749927 · inbound

Who Gets the Kidney? Human-AI Alignment, Indecision, and Moral Values cites this paper.

Who Gets the Kidney? Human-AI Alignment, Indecision, and Moral Values Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-19T14:13:05.844927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T14:12:42.610994Z digest=sha256:aaf30711e9ea7c3a36cc5f00c6e929c7af2ff3328fd74997d19d2e47dccd29a9

Observation 4e83c55c-d7f3-48c3-ae9d-895aaf778169 · inbound

Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling cites this paper.

Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:27:14.809163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T09:23:44.372077Z digest=sha256:1c3d97afa0ad118f98f1d7f8d20ce39b0ca455ff7148627635e057f80e582f3a