Normative Conformity in Language Models

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This field examines how language models respond to social norms, peer consensus, authority, group identity, and local conversational cues—and whether those responses reflect norm understanding or simple imitation. Researchers use controlled peer-pressure question-answering tasks, social dilemmas, group-chat norm adaptation benchmarks, and multi-agent simulations, often varying whether the prevailing answer is correct and whether a norm is explicit or inferred. Models can change answers under social pressure, including toward incorrect claims, while reasoning prompts sometimes help; behavior also varies with culture, identity, and context. A central challenge is balancing resistance to misleading influence with receptivity to correct advice, while distinguishing a model’s stated conformity from its underlying beliefs or genuine normative competence.

Latest papers

29 papers5 papers in the last four weeks, up 67% on the four weeks before. 0.0% of all new papers.

A Quantitative Approach to Asch Conformity in Frontier Large Language Models
Oct 27, 2026Senthil Rajasekaran, Stylianos Loukas VasileiouNormative Conformity in Language Models LLM Evaluation
Université libre de Bruxelles · New Mexico State University
TenetBench: A Clause-Anchored Russian Corpus for Evaluating Language Models against Professional Codes of Ethics
Oct 21, 2026Yegor Anichkov, Valery Vinogradov, Andrey Furov +2Language Model Safety Evaluation LLM Safety Benchmarks
Trusted AI Research Center, RAS, Moscow, Russia. · Center for Applied Artificial Intelligence, Institute of Social Sciences, Moscow, Russia.
Drivers of LLM Consensus Formation Under Competing Incentives: A Simulation Study
Oct 14, 2026Isabel Jones, Matthew Edwards, Janina A. HoffmannMulti-Agent Consensus Multi-Agent LLM Systems
University of Bristol Bristol, United Kingdom · University of Bath Bath, United Kingdom
Why LLM Agents Favor Their Group: Stakes, Observed Norms, and Reputation
Oct 7, 2026Yujiao ChenSocial Bias in Language Models Normative Conformity in Language Models
Massachusetts Institute of Technology · Primitive Labs
Reading the Room: Foundations, Design, and Challenges of Normative Competence in LLMs
Oct 7, 2026Andrea Wynn, Harsh Satija, Nathan Baek +3Normative Conformity in Language Models Social Reasoning
Nathan · Johns Hopkins University · Vector Institute
Silent Dissent: LLM Agents That Yield to the Majority Still Represent Their Original Premise
Oct 2, 2026Ziang Ni, Peng ZouNormative Conformity in Language Models Multi-Agent Debate
Sun Yat-sen University Guangzhou, China
LLMs Trust Their Own: Identity-Dependent Conformity in Multi-Agent Systems
Sep 27, 2026Liron Soffer, Ravid Shwartz-Ziv, Chen ShaniNormative Conformity in Language Models Social Bias in Language Models
Tel-Aviv University · New York University
Directing large language models to follow the letter or spirit of the law
Sep 19, 2026Peng Qian, Andrew Li, Sam Chen +3Legal Reasoning Normative Conformity in Language Models
Department of Psychology, Harvard University · Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University · Taub Faculty of Computer Science, Technion — Israel Institute of Technology
Conformity Breaks Conformal Prediction
Sep 3, 2026Yibo Hu, Hanyu SuConformal Prediction Adversarial Attacks on LLMs
Illinois Institute of Technology
Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales
Aug 13, 2026Long Hoang Nguyen, Brice Valentin Kok-Shun, Guangyu Du +1Moral Reasoning in Language Models Normative Conformity in Language Models
1Technical University of Munich · University of Auckland
Social Pressure Breaks Majority Voting in LLM Safety Panels
Aug 5, 2026Yibo Hu, Jiaming QuNormative Conformity in Language Models Safety Filtering
Illinois Institute of Technology · Amazon
Everyone Conforms, No One Believes: Pluralistic Ignorance in LLM Agent Populations
Aug 3, 2026Yashwanth YSMulti-Agent LLM Systems Normative Conformity in Language Models
Language Technologies Institute, Carnegie Mellon University, Pittsburgh, USA
Conformity Mitigations in Large Language Models Lie on a Single Resistance-Receptivity Frontier
Aug 3, 2026Zafar Hussain, Kristoffer NielboLLM Evaluation Normative Conformity in Language Models
Aarhus University
Most LLM Conformity Needs No Speaker: Measuring the Speaker-Free Floor in Peer-Pressure Benchmarks
Jul 6, 2026Yibo Hu, Jiaming QuLLM Evaluation Normative Conformity in Language Models
Illinois Institute of Technology · Amazon
LoSoNA: A Benchmark for Local Social Norm Adaptation in Group Conversations
Jun 12, 2026Mateusz Winiarek, Maksymilian Bilski, Mateusz JacniackiNormative Conformity in Language Models Pragmatic Reasoning in Language Models
Humalike Research
Whose Norms? Disentangling Cultural and Personal Alignment in Large Language Models
Jun 5, 2026Angana Borah, Isabelle Augenstein, Rada MihalceaLLM Alignment Normative Conformity in Language Models
University of Michigan - Ann Arbor · University of Copenhagen
Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity
Jun 1, 2026Jiaming Qu, Lucheng Fu, Yibo HuMulti-Agent LLM Systems Normative Conformity in Language Models
Amazon · Georgia Institute of Technology · Illinois Institute of Technology
Can LLMs Emulate Human Belief Dynamics?
May 5, 2026Adiba Mahbub Proma, Neeley Pate, James N. Druckman +3Opinion Dynamics Normative Conformity in Language Models
Department of Computer Science University of Rochester · Department of Political Science University of Rochester · Department of Physics and Astronomy University of Rochester
Large Language Models Exhibit Normative Conformity
Apr 21, 2026Mikako Bito, Keita Nishimoto, Kimitaka Asatani +1Normative Conformity in Language Models Social Bias in Language Models
The University of Tokyo
Blind Refusal: Language Models Refuse to Help Users Evade Unjust, Absurd, and Illegitimate Rules
Apr 3, 2026Cameron Pattison, Lorenzo Manuali, Seth LazarRefusal Behavior in Language Models Refusal Mechanisms in Language Models
Department of Philosophy, Vanderbilt University · Department of Philosophy, University of Michigan · School of Government and Policy, Johns Hopkins University
Do LLM-Driven Agents Exhibit Engagement Mechanisms? Controlled Tests of Information Load, Descriptive Norms, and Popularity Cues
Mar 21, 2026Tai-Quan Peng, Yuan Tian, Songsong Liang +2Large Language Model-Based Social Simulation Human Behavior Simulation
Department of Communication, Michigan State University, USA · College of Computer Science and Technology, Zhejiang University, China · School of Software Technology, Zhejiang University, China
Same Voice, Different Lab: On the Homogenization of Frontier LLM Personalities
Mar 20, 2026Avinash Krishna, Kalyana Chadalavada, Unso Eun Seo JoPersonality Modeling in Language Models Behavioral Consistency of LLM Agents
Independent · Anthropic · Cornell University
GAIN: A Benchmark for Goal-Aligned Decision-Making of Large Language Models under Imperfect Norms
Mar 19, 2026Masayuki Kawarada, Kodai Watanabe, Soichiro MurakamiLLM Decision-Making LLM Evaluation
CyberAgent
Alignment Makes Language Models Normative, Not Descriptive
Mar 17, 2026Eilam Shapira, Moshe Tennenholtz, Roi ReichartLLM Alignment Preference Alignment
Technion – Israel Institute of Technology
BenchPreS: A Benchmark for Context-Aware Personalized Preference Selectivity of Persistent-Memory LLMs
Mar 17, 2026Sangyeon Yoon, Hyesoo Hong, Wonje Jeung +5Personalized Language Models LLM Evaluation
Yonsei University · LG AI Research
How do Role Models Shape Collective Morality? Exemplar-Driven Moral Learning in Multi-Agent Simulation
Mar 14, 2026Junjie Liao, Huacong Tang, Zhou Ziheng +2Normative Conformity in Language Models Imitation Learning
Beijing Normal University · University of California, Los Angeles · Peking University
How Do Language Models Process Ethical Instructions? Deliberation, Consistency, and Other-Recognition Across Four Models
Mar 11, 2026Hiroki FukuiMoral Reasoning in Language Models LLM Safety Alignment
Research Institute of Criminal Psychiatry / Sex Offender Medical Center · Department of Neuropsychiatry, Kyoto University
LiveCultureBench: a Multi-Agent, Multi-Cultural Benchmark for Large Language Models in Dynamic Social Simulations
Mar 2, 2026Viet-Thanh Pham, Lizhen Qu, Thuy-Trang Vu +2AI Agent Benchmarks Cross-Cultural Language Model Evaluation
Department of Data Science & AI, Monash University
Agency and Architectural Limits: Why Optimization-Based Systems Cannot Be Norm-Responsive
Feb 26, 2026Radha SarmaAI Governance AI Alignment

Oct 27, 2026J/K move · Enter open · S save

A Quantitative Approach to Asch Conformity in Frontier Large Language Models

Senthil Rajasekaran, Stylianos Loukas Vasileiou

Université libre de Bruxelles · New Mexico State University

Normative Conformity in Language Models LLM Evaluation

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The Asch conformity experiment has recently gained considerable attention as a way of measuring conformity in large language models (LLMs). While previous studies have focused on demonstrating conformity in LLMs, our work adds a further quantitative layer to this approach. Instead of sampling a frontier LLM on a suite of questions, our approach samples a single question repeatedly, leveraging the probabilistic nature of LLMs to produce a distribution of answers. In doing so, we can compare the distributions of answers before and after the model is presented with the manufactured consensus. Our experiments confirm that frontier LLMs do conform, reinforcing prior literature, and, through our distribution-to-distribution comparisons, provide additional quantitative data on the conditions that lead to conformity and the degree to which it occurs.