Bias in LLM-as-a-Judge

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This field examines how automated judges can favor certain answers for reasons unrelated to quality, including response order, writing style, verbosity, model identity, language, and demographic or cultural cues. Researchers use controlled counterfactual tests and benchmarks such as MT-Bench, RewardBench, and multilingual or domain-specific evaluation sets to measure when judgments change and whether they match human ratings. Mitigation approaches include randomizing presentation, adding rubrics and reference answers, calibrating scores with human comparisons, combining judges robustly, and training models to separate relevant evidence from distracting cues. A central challenge is that repeatable judgments and agreement among models do not guarantee validity, while interventions that reduce bias can also erase real quality differences or legitimate differences in human preferences.

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118 papers21 papers in the last four weeks, up 11% on the four weeks before. 0.1% of all new papers.

Style over Substance? Linguistic Bias in LLM-based Peer Review Copy title
Oct 26, 2026Sai Suresh Macharla Vasu, Sumedh Santosh Joshi, Philipp Christmann +6Linguistic Bias in Language Models Bias in LLM-as-a-Judge
CISPA Helmholtz Center for Information Security · German Research Center for Artificial Intelligence (DFKI) · University of Technology Nuremberg +1
Tampered ML: Evaluating LLM Judgment of Machine Learning Research
Oct 23, 2026Soroush Ebadian, Parand A. Alamdari, Joe Benton +1LLM Evaluation Scientific Reasoning in Language Models
Anthropic Fellows Program · Anthropic
The Missing Compliance Class: LLM Graders That Collapse Jailbreak Success, and a Free Check
Oct 17, 2026Ruqiya Bin SafiJailbreak Attack Evaluation LLM-as-a-Judge
Independent Researcher
Screening LLM Judges Without Ground Truth: A Preliminary Evaluation of an AI Dental Hygiene Coach
Oct 17, 2026William DeShong, Barath Kannan, Auberon Palma +3LLM-as-a-Judge LLM Reliability
The Judge Can Debias Itself: Awareness and Self-Debiasing for Reliable LLM-as-a-Judge
Oct 16, 2026Youbing Yin, Jingyu Wu, Anoop Kumar +3Bias in LLM-as-a-Judge LLM-as-a-Judge
Capital One
A Plausible Explanation Is Enough to Mislead Multimodal Judges
Oct 15, 2026Anglin Cai, Zhiqi Wang, Xiaozhi Yang +3Bias in LLM-as-a-Judge Vision-Language Model-as-a-Judge
Northwestern University · The Pennsylvania State University · University of Pennsylvania +1
Did the LLM Answer the Question? A Semantic Reconstruction Game for Jailbreak Evaluation
Oct 13, 2026Liam Davis, Romain Emil-Popescu, Suman JanaJailbreak Attack Evaluation LLM Safety Evaluation
Amherst College · Columbia University
Judges Follow the Reference: The Derivation Gap in Verifying Tool-Call Arguments
Oct 13, 2026Linhai Ma, Yan Wang, Lingfei Qian +2Tool-Use Evaluation LLM-as-a-Judge
The Fin AI, USA · Yale University, USA · Cardiff University, UK
PRISM: Calibrating Black-Box Judges with Counterfactual Probes
Oct 13, 2026Kakei Yamamoto, So KurokiLLM-as-a-Judge Language Model Generation Evaluation
EECS, Massachusetts Institute of Technology · Sakana AI
Cheap, Consistent, Calibrated, but Biased? Typed Decision Models as Judges
Oct 13, 2026Fabian Lukassen, Christoph Weisser, Alexander SilbersdorffBias in LLM-as-a-Judge LLM-as-a-Judge
University of Göttingen · Bielefeld University of Applied Sciences and Arts (HSBI)
A CaLLM Judge is a Better Judge: Mitigating Bias in LLM-as-a-judge
Oct 13, 2026Cesare Barbera, Luca Stradiotti, Lorenzo Cascioli +6Bias in LLM-as-a-Judge LLM-as-a-Judge
University of Pisa · University of Trento · KU Leuven +1
Executable Prefix Values for Locating Agent Failures
Oct 13, 2026Bingyu Shen, Jiaqi Tang, Lan Wei +3Agent Failure Analysis LLM Agent Evaluation
Independent Researcher · Department of Computer Science and Technology, Kean University, Union, NJ, USA · Bellini College of Artificial Intelligence, Cybersecurity and Computing, University of South Florida, Tampa, FL, USA
The Format is the Filter: Scoring Format Fixes What an LLM Judge Can Express
Oct 12, 2026Lovedeep Gondara, Jekaterina Novikova, Sagarika Suresh +2LLM-as-a-Judge Bias in LLM-as-a-Judge
The Vanguard Group, Inc.
All Verdicts are Not Equal: Rethinking LLM Judge Reliability
Oct 8, 2026Vineet Kumar, Darshita Rathore, Anindya MoitraLLM-as-a-Judge LLM Evaluation
PayPal Artificial Intelligence PayPal, Bengaluru, India
Adversarial Cues in Decision Models Used as Judges: The Role of Request Presentation
Oct 8, 2026Hongliang LiuLLM-as-a-Judge Bias in LLM-as-a-Judge
Independent Researcher
Reliability of LLM Judges for Evaluating Entity Alignment
Oct 7, 2026Vaibhava Lakshmi Ravideshik, Mayank KejriwalKG Entity Alignment LLM-as-a-Judge
University of Michigan, Ann Arbor · Information Sciences Institute, University of Southern California
A Systematic Investigation of Bias in Large Language Models for Advertising Relevance
Oct 6, 2026Weiwei Wang, Yinchuan Xu, Jialu Gao +2Bias in LLM-as-a-Judge Language Model Bias Evaluation
Microsoft
Will the Judge Flip? Predicting Position-Sensitive LLM Judgments from Residual Stream Activations
Oct 5, 2026Hashmath Shaik, Gnaneswar Villuri, Alex DoboliLLM Evaluation LLM-as-a-Judge
Department of Electrical and Computer Engineering Stony Brook University Stony Brook, NY 11794, USA
Not Self-Decidable: LLMs Cannot Draw the Boundary of What an Agent Verifier Can Check
Oct 3, 2026Anthony RhodesLLM Agent Verification Runtime Enforcement for AI Agents
Confidential Core AI
CuBEs: Culturally-Situated Behavioral Evaluations and the Limitations of Culture-Blind LLM Judges
Oct 2, 2026Hoda Ayad, Tanu Mitra, Abhishek MukherjiLLM Evaluation Cross-Cultural Language Model Evaluation
University of Washington · Centific
Right Order, Wrong Scale: Auditing LLM Judges for Occupational AI Measurement
Oct 1, 2026Harry Lyu, Neil ThompsonLLM-as-a-Judge LLM Evaluation
Massachusetts Institute of Technology
Do MLLM Judges Judge the Edit? Auditing Bias in Image Editing Evaluation with Verified Quality Preservation
Oct 1, 2026Yuan Huang, Zirui Song, Xiuying ChenVLM Robustness LLM-as-a-Judge
Northeastern University · Mohamed bin Zayed University of Artificial Intelligence
LLMAdBench: A Human Preference Benchmark for Advertising in LLM Responses
Sep 26, 2026Rui Ai, Yuqing Liu, Sitao Qiu +14Language Model Generation Evaluation Human Preference Modeling
Massachusetts Institute of Technology · University of Michigan, Ann Arbor · Shanghai Jiao Tong University +7
Opening LLM Judges: Recovering Preference Signals Beyond the Final Verdict
Sep 26, 2026Sourabrata Mukherjee, Sunayana SitaramLLM-as-a-Judge Bias in LLM-as-a-Judge
Microsoft Research
Is the Judge Its Twin? Post-training makes a model's writing more predictable but barely moves its taste, as a judge, toward predictable writing
Sep 26, 2026Arman Nik Khah, Arvin BahreiniLanguage Model Post-Training Language Model Generation Evaluation
The University of Texas at Dallas · University of Oregon
DIAL: Position-Debiased LLM Judges with Adaptive Human Preference Calibration
Sep 25, 2026Zesheng Cai, Yingqi Fan, Sichang Chen +1LLM-as-a-Judge Bias in LLM-as-a-Judge
The University of Hong Kong · Sun Yat-sen University
Accounting for Bias Enables Sustainable LLM Evaluation
Sep 25, 2026Harshita Katoch, David Antony Selby, Gerrit Großmann +1LLM Evaluation Bias in LLM-as-a-Judge
Department of Computer Science, University of Kaiserslautern–Landau (RPTU), Germany · Data Science and its Applications, German Research Centre for Artificial Intelligence (DFKI), Germany
How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats
Sep 20, 2026Ian ArawjoStatistical Hypothesis Testing LLM Evaluation
Department of Computer Science and Operations Research (DIRO) Université de Montréal Montréal, Quebec, Canada
Summarization Bias: The Directional Collapse of Objective Projection into Told-Mode Labels in Large Language Models --- A Conceptual Framework and Registered Test Protocol
Sep 17, 2026Levent BulutLanguage Model Bias Evaluation Linguistic Bias in Language Models
Independent Researcher
Who Judges Matters: Measuring Family-Conditioned Preference in LLM-as-Judge Panels
Sep 15, 2026David Ababio Awuni, Luke E. K. Achenie, Benjamin Tei Partey +2LLM-as-a-Judge Pairwise Preference Evaluation

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Style over Substance? Linguistic Bias in LLM-based Peer Review Copy title

Sai Suresh Macharla Vasu, Sumedh Santosh Joshi, Philipp Christmann, Ivaxi Sheth+5

CISPA Helmholtz Center for Information Security · German Research Center for Artificial Intelligence (DFKI) · University of Technology Nuremberg+1

Linguistic Bias in Language Models Bias in LLM-as-a-Judge Automated Peer Review

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The number of paper submissions to major AI conferences has increased dramatically in recent years, substantially increasing the peer-review workload of researchers. At the same time, large language models (LLMs) are increasingly used to support peer review, both by individual reviewers and by conference organizations. While LLM capabilities have improved considerably, their evaluations may be influenced by linguistic characteristics that are unrelated to scientific content. In this work, we introduce a controlled experimental framework for studying such effects by systematically perturbing the linguistic style of research papers. Specifically, we rewrite papers to exhibit (i) linguistic features associated with native or non-native English writing, and (ii) high- or low-confidence linguistic features. To construct these interventions, we derive fine-grained rewriting instructions grounded in the linguistic literature and apply them using LLMs. Crucially, our interventions are designed to preserve the underlying scientific content. We then evaluate the resulting papers using different LLM reviewers. Our experiments expose a critical vulnerability in LLM-based peer review: reviewers systematically reward confident rhetoric independent of scientific content, raising serious concerns about the robustness of their assessments.