Relative Bias: A Comparative Framework for Quantifying Bias in LLMs | Paper Citation Record

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This paper cites https://aws.amazon.com/bedrock, 2024.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs https://aws.amazon.com/bedrock, 2024

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs https://www.deepseek.com, 2024

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs https://aistudio.google.com, 2024

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs https://www.meta.ai, 2024

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Tukey’s honestly significant difference (hsd) test

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This paper cites Mitigating Language-Dependent Ethnic Bias in BERT.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Mitigating Language-Dependent Ethnic Bias in BERT

Reference 6

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Amazon bedrock guardrails

Reference 7

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This paper cites A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Non-Determinism of "Deterministic" LLM Settings

Reference 9

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Language models are few-shot learners

Reference 10

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This paper cites FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders

Reference 11

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs OR-Bench: An Over-Refusal Benchmark for Large Language Models

Reference 12

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Bert: Pre-training of deep bidi- rectional transformers for language understanding

Reference 13

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This paper cites Bold: Dataset and metrics for measuring biases in open-ended language generation.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Bold: Dataset and metrics for measuring biases in open-ended language generation

Reference 14

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Disclosure and Mitigation of Gender Bias in LLMs

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 16

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Alpacafarm: A simulation framework for methods that learn from human feedback

Reference 17

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This paper cites Meta ai refusing to answer questions related to politicians and par- ties ahead of elections in india, 2024.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Meta ai refusing to answer questions related to politicians and par- ties ahead of elections in india, 2024

Reference 18

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This paper cites Toy Models of Superposition.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Toy Models of Superposition

Reference 19

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs ROBBIE: Robust Bias Evaluation of Large Generative Language Models

Reference 20

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This paper cites Bias and fairness in large language models: A survey.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Bias and fairness in large language models: A survey

Reference 21

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Pairwise multiple comparison procedures with unequal n’s and/or variances: a monte carlo study

Reference 22

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models

Reference 23

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Debiasing pre-trained language models via efficient fine-tuning

Reference 24

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs A Survey on LLM-as-a-Judge

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs We tried out deepseek

Reference 26

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Auto-debias: Debiasing masked language models with automated biased prompts

Reference 27

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Does Prompt Formatting Have Any Impact on LLM Performance?

Reference 28

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Measuring Massive Multitask Language Understanding

Reference 29

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Reducing Sentiment Bias in Language Models via Counterfactual Evaluation

Reference 30

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Perspective api, 2025

Reference 31

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Debiasing Pre-trained Contextualised Embeddings

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Pretraining language models with human preferences

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Measuring Bias in Contextualized Word Representations

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Equivalence tests: A practical primer for t tests, correlations, and meta-analyses

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Fairness Testing of Large Language Models in Role-Playing

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Alpacaeval: An automatic evaluator of instruction-following models, 2023

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Towards Debiasing Sentence Representations

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Towards understanding and mitigating social biases in language models

Reference 40

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Holistic Evaluation of Language Models

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Does Gender Matter? Towards Fairness in Dialogue Systems

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Lmarena: Open platform for crowdsourced ai benchmarking

Reference 44

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Azure openai service content filtering

Reference 45

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

Reference 46

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 47

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Honest: Measuring hurtful sentence completion in language models

Reference 48

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Large Language Model (LLM) Bias Index -- LLMBI

Reference 49

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs GPT-4 Technical Report

Reference 50

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs The perils and promises of fact-checking with large language models

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs MBIAS: Mitigating Bias in Large Language Models While Retaining Context

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Rails

Reference 53

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 54

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Does deepseek censor its answers? we asked 5 questions on sensitive china top- ics

Reference 55

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Introduction to probability models

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Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in nlp

Reference 57

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This paper cites A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability

Reference 58

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Observation 5e59c711-700f-44cf-b5de-bb0b683911ad · outbound

This paper cites Large Language Model Alignment: A Survey.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Large Language Model Alignment: A Survey

Reference 59

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Observation 99c86017-6745-4a4d-935a-2c35e05ab2d2 · outbound

This paper cites Prompting GPT-3 To Be Reliable.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Prompting GPT-3 To Be Reliable

Reference 60

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This paper cites The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism

Reference 61

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Observation 8d7614bc-8ed8-49dc-a1c9-73f71e6fe84a · outbound

This paper cites Analysis of variance (anova).Chemometrics and intelligent laboratory systems, 6(4):259–272, 1989.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Analysis of variance (anova).Chemometrics and intelligent laboratory systems, 6(4):259–272, 1989

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:29.270644Z

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Observation 118dff2d-0753-4dd6-9bc8-c24c37b20be7 · outbound

This paper cites One Embedder, Any Task: Instruction-Finetuned Text Embeddings.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs One Embedder, Any Task: Instruction-Finetuned Text Embeddings

Reference 63

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This paper cites Grok 3 appears to have briefly censored unflattering mentions of trump and musk, 2025.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Grok 3 appears to have briefly censored unflattering mentions of trump and musk, 2025

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:29.089474Z

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Observation 2554893e-4bef-45d0-a450-5f78479ec2bc · outbound

This paper cites A Robust Bias Mitigation Procedure Based on the Stereotype Content Model.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs A Robust Bias Mitigation Procedure Based on the Stereotype Content Model

Reference 65

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This paper cites Llm leaderboard, 2025.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Llm leaderboard, 2025

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:28.824739Z

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This paper cites The dark side of generative artificial intelligence: A critical analysis of controversies and risks of chatgpt.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs The dark side of generative artificial intelligence: A critical analysis of controversies and risks of chatgpt

Reference 67

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Observation 9f96eb18-a34c-4bf0-a191-435305c35cf0 · outbound

This paper cites Large Language Models are not Fair Evaluators.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Large Language Models are not Fair Evaluators

Reference 68

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This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 69

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This paper cites Mmlu-pro: A more robust and challenging multi-task language understanding benchmark.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Mmlu-pro: A more robust and challenging multi-task language understanding benchmark

Reference 70

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This paper cites All of statistics: a concise course in statistical inference.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs All of statistics: a concise course in statistical inference

Reference 71

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Observation 91b9fee3-05ff-4342-92ce-8b9e21dd9b7b · outbound

This paper cites Measuring and Reducing Gendered Correlations in Pre-trained Models.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Measuring and Reducing Gendered Correlations in Pre-trained Models

Reference 72

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Observation a60db2fb-3c48-4f80-9cb9-f55dad0982d9 · outbound

This paper cites The generalization of ‘student’s’problem when several different population varlances are involved.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs The generalization of ‘student’s’problem when several different population varlances are involved

Reference 73

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Observation fdbc3afe-5b05-4fca-8ae5-f5e313faf5b8 · outbound

This paper cites Livebench: A challenging, contamination-free LLM benchmark.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Livebench: A challenging, contamination-free LLM benchmark

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:28.344544Z

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Observation 8ea27ce6-d086-4b6b-a7ff-3aa3a6784b2c · outbound

This paper cites This powerful new chatbot works great—unless you ask about china, 2025.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs This powerful new chatbot works great—unless you ask about china, 2025

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:28.133989Z

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Observation 8a853731-12f4-440a-ad5f-9c07a3867568 · outbound

This paper cites Compensatory debiasing for gender imbalances in language models.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Compensatory debiasing for gender imbalances in language models

Reference 76

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Observation febd100a-0219-41c8-9fd7-2d4b3b64b0cb · outbound

This paper cites Order Matters in Hallucination: Reasoning Order as Benchmark and Reflexive Prompting for Large-Language-Models.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Order Matters in Hallucination: Reasoning Order as Benchmark and Reflexive Prompting for Large-Language-Models

Reference 77

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Observation c813e29d-1692-4e8f-b78b-f080f31fb17d · outbound

This paper cites Large language model as attributed training data generator: A tale of diversity and bias.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Large language model as attributed training data generator: A tale of diversity and bias

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:27.777884Z

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Observation b497a7b1-6cbe-42cb-8f8f-6b4ef4ab3a57 · outbound

This paper cites Wider and Deeper LLM Networks are Fairer LLM Evaluators.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Wider and Deeper LLM Networks are Fairer LLM Evaluators

Reference 79

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Observation a85f9f47-6d90-443d-ada6-a810ed66b41e · outbound

This paper cites Explainability for large language models: A survey.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Explainability for large language models: A survey

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:25.991115Z

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Observation 0186f663-106e-4d56-b52e-bc8829b8046b · outbound

This paper cites GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs GPTBIAS: A Comprehensive Framework for Evaluating Bias in Large Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:26.108646Z

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Observation 36bb37d0-4df9-483f-8d44-fdea6d64eb38 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:26.214959Z

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Observation 3483dc30-69ef-424c-8e25-217f447deeca · outbound

This paper cites Lima: Less is more for alignment.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs Lima: Less is more for alignment

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:26.258317Z

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Observation 13ab7a7b-870e-4cd0-a527-687eedc76b63 · outbound

This paper cites {question}.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs {question}

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:27.596932Z

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Observation 5ba7887e-9682-456e-966d-43e54c02743d · outbound

This paper cites A.3 Bias Criteria Table Score Description 1 Fully neutral and factual.

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs A.3 Bias Criteria Table Score Description 1 Fully neutral and factual

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:12:27.434147Z

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