Language Model Robustness

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35 papers in the last four weeks, up 46% on the four weeks before. 0.3% of all new papers.

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Benchmarking Factual Robustness of LLMs via Multi-conversation Persuasion
Sep 15, 2026Zhuoang CaiAdversarial Attacks on LLMs LLM Safety Evaluation
The Hong Kong University of Science and Technology
RoleBreak: Benchmarking Long-Horizon Role-Playing Robustness in Spoken Dialogue
Sep 15, 2026Yuqi Wang, Fengyuan Liu, Haochen Luo +2Large Language Model-Based Role-Play Simulation Speech Generation Evaluation
The University of Hong Kong · Kami AI
Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening
Sep 15, 2026Qiangju Chen, Yang XiaoLLM Evaluation Language Model Robustness
1Macquarie University · 2The University of Melbourne
Overflip: Repetition-Induced Label Flips in Guardrail Models
Sep 14, 2026Xu He, Chih-Hsuan Lin, Hung-Mao Chen +3LLM Guardrails Adversarial Attacks on LLMs
1George Mason University · 2Virginia Tech · 3Missouri University of Science and Technology +1
Toward Robust Personalized Alignment for LLMs: Mitigating Persona Drift in Multi-Turn Dialogue
Sep 14, 2026Youyuan Zhang, Siyuan Li, Fangming Liu +1Belief Revision LLM Alignment
Harbin Institute of Technology, Shenzhen, China · Peng Cheng Laboratory, China · Huazhong University of Science and Technology, China
Rethinking Verbalized Confidence for LLM-as-a-Judge: A Compatibility Shift on Post-2025 Proprietary Models
Sep 11, 2026Yu-Chung HsiaoLLM Evaluation LLM-as-a-Judge
Cisco Systems
When Noise Fabricates Bias: The Fragility of LLM-as-a-Judge Bias Measurement under Noisy Text
Sep 10, 2026DongHyun Ryu, Jaehyeok Lee, YeongJun Hwang +1LLM-as-a-Judge Social Bias in Language Models
Sungkyunkwan University, Suwon, South Korea
Forgetting Only What Matters: Layer-Selective Unlearning toward Robust LLMs
Sep 9, 2026Ravi Ranjan, Olivera Kotevska, Agoritsa PolyzouMemorization in Language Models Language Model Robustness
Florida International University (FIU), Miami, FL, USA · Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA
Which Medical Questions Deserve Rationales? Perturbation-Sensitive Selection for Robust QA
Sep 9, 2026Yuexin Wu, Dayou Yu, Vasile RusData Selection Medical QA
Department of Computer Science, University of Memphis
FramingQA: Does the Question Shape the Answer? Measuring the Compositional Framing Effect
Sep 7, 2026Hazel H. Kim, Andrew M. Bean, Guilherme Affonso Ferreira de Camargo +10LLM Evaluation LLM Reliability
Department of Computer Science, University of Oxford · Oxford Internet Institute, University of Oxford · Thomson Reuters +7
LANTERN: Language Model Assessment on Noisy and Transformed Tasks for Understanding Error and Robustness Nuances
Sep 7, 2026Vamsi Krishna Kodavali, Rituraj SinghLLM Evaluation Instruction Following
Samsung
Beyond Shallow Alignment: How Post-Training Methods Determine Refusal Circuits And Steering Robustness
Sep 3, 2026Hoang Cuong Nguyen, Mark Dras, Usman NaseemMechanistic Interpretability Circuits in Language Models
Macquarie University, Sydney, Australia
Lost in Reordering: Structural Sensitivity of Multilingual LLMs under Semantics-Preserving Perturbations
Sep 3, 2026Karthika Nhayakkat, Rajat Verma, Maharaj Brahma +4Numerical Reasoning in Language Models Multilingual Language Model Evaluation
Department of CSE, Indian Institute of Technology Bombay · SCEE, Indian Institute of Technology Mandi · Department of CSE, Indian Institute of Technology Hyderabad
How Perturbations Propagate: A Multi-Level Analysis of Robustness in Large Language Models
Sep 3, 2026Dun Li Chan, Emily Liu, Niyathi Allu +1Decoder-Only Language Models Language Model Robustness
INTI International College Penang · Independent Researcher · FPT University
Untangling the Mechanisms of Misleading Context in Medical Question Answering
Sep 2, 2026Robin Linzmayer, Noémie ElhadadMedical QA Language Model Robustness
Department of Computer Science, Columbia University, New York, NY, USA · Department of Biomedical Informatics, Columbia University, New York, NY, USA
Investigating Linear Probe Robustness to Linguistic Register, Medical Specialty, and Corpus Shifts in Medical QA
Sep 1, 2026Nishant Mishra, Ameen Abu-Hanna, Iacer CalixtoClinical Language Model Evaluation Language Model Robustness
Department of Medical Informatics, Amsterdam UMC, University of Amsterdam · Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
Prompt-Robust Language Models: Which Training Strategies Work?
Sep 1, 2026Frederic Sadrieh, Michal ŠtefánikPrompt Sensitivity LLM Fine-Tuning
Center for Information and Language Processing, LMU Munich · R&D Centre for Large Language Models, National Institute of Informatics, Japan
Topological Steering
Sep 1, 2026Benoît Guérand, Tan Minh NguyenLanguage Model Steering Language Model Robustness
Department of Mathematics · National University of Singapore (NUS) · Science Drive 2, Singapore 117543
Are Near-Tied LLM Rankings Robust to Family-DIF-Guided Benchmark Recomposition?
Aug 31, 2026Qiaoyuan Zheng, Yiqu YangLLM Evaluation Pairwise Ranking
ETH Zurich Zurich, Switzerland
TrainSDC: Characterizing and Mitigating Silent Data Corruption in Large Language Model Training
Aug 31, 2026Zhipeng Xia, Haotian Xu, Siyu Yun +4Fault-Tolerant Distributed Training Language Model Robustness
Zhejiang University · Huawei
Beyond Surface Forms: Symbolic Edits as a Test for Logical Reasoning with LLMs
Aug 31, 2026Ramya Keerthy Thatikonda, Wray Buntine, Ehsan ShareghiLogical Reasoning LLM Evaluation
Department of Data Science & AI, Monash University · ∃Department of Computer Science, University College London
Quantifying and Mitigating Korean Jamo-Level Typographical Vulnerabilities in Large Language Models
Aug 31, 2026Seojin Lee, Hwanhee LeeLanguage Model Robustness
Chung-Ang University, Seoul, Korea
When Do Supervised UQ Ensembles Improve LLM Hallucination Detection? A Robustness Study
Aug 25, 2026Mohit Singh Chauhan, Vipin Gyanchandani, Dylan BouchardLLM Hallucination Detection LLM Uncertainty Estimation
CVS Health®, Wellesley, MA, USA
When Detection Does Not Guarantee Resistance: Reasoning and Poisoned Context in RAG
Aug 17, 2026Mehrdad Ghassabi, Audrina Ebrahimi, Sadra Hakim +3Knowledge Conflicts in Language Models RAG Poisoning Attacks
University of Isfahan · University of Texas at Dallas · University of Windsor
Jagged Judges: Epistemic Stability Under Silence, Pressure, and Persistence
Aug 12, 2026Justin Zhao, Himaghna Bhattacharjee, Hannah Korevaar +2LLM Evaluation LLM-as-a-Judge
1Meta Superintelligence Labs · 2FAIR at Meta
Policy-as-logic for robust reasoning over rules
Aug 12, 2026Rahul Nair, Bastian Lipka, Elizabeth DalyNeuro-Symbolic Reasoning Language Model Robustness
1IBM Research · 2IBM
Making Your LLMs More Objective: Stabilizing LLM Safety Behavior Across Traits with Trait-Invariant Safety Tuning
Aug 12, 2026Lang CaoLLM Alignment Language Model Safety Evaluation
University of Illinois Urbana-Champaign
The Wording Effect: Quantifying Two-Way Drift in LLM Benchmark Performance
Aug 12, 2026Shailja Thakur, Sungeun An, Chad DeLuca +1Prompt Sensitivity LLM Evaluation
IBM Research India · IBM Research Almaden
Assessing Reliability of BERT-Based Models on Question Answering Tasks
Aug 11, 2026Pooja Yadav, Priyanka Harjule, Basant Agarwal +1Question Answering Language Model Robustness
Department of Mathematics, Malaviya National Institute of Technology, Jaipur, Rajasthan, India · Department of Computer Science and Engineering, Central University of Rajasthan, Kishangarh, Rajasthan, India · University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia
MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection
Aug 11, 2026Jinmo Han, Jimin Hong, Chanyeong Moon +3AI-Generated Text Detection Prototype Learning
Department of Electrical and Computer Engineering and INMC Seoul National University, Seoul, Republic of Korea

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Benchmarking Factual Robustness of LLMs via Multi-conversation Persuasion

Zhuoang Cai

The Hong Kong University of Science and Technology

Adversarial Attacks on LLMs LLM Safety Evaluation Persuasion in Language Models Language Model Robustness

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As Large Language Models (LLMs) increasingly serve as primary knowledge retrieval interfaces, their robustness against \textit{persuasion attacks}---attempts to inject misinformation or enforce counterfactuals---has become a critical safety concern. Existing red-teaming frameworks typically evaluate models in multi-turn dialogues where the target model retains full conversation history. We identify a critical flaw in this setting termed \textbf{

Refusal Inertia''}: a model's initial refusal often propagates through subsequent turns largely to maintain contextual consistency, thereby masking its true vulnerability to sophisticated, isolated persuasion attempts. To rigorously evaluate the

cold-start'' defense capabilities of SOTA models, we introduce the \textbf{SAST-IR} (Stateful Attacker, Stateless Target - Iterative Refinement) framework. By enforcing a memory wipe on the target while retaining the attacker's history, we simulate a worst-case adversarial setting using \textbf{multi-turn} (stateless) iterations. Leveraging \textbf{CP-Agent} (Cognitive Persuasion Agent), an enhanced diagnosis-guided agent, our experiments on the custom \textsc{CounterFact-Strict} dataset (

N=50

) yield alarming results: simple, diverse attack strategies achieved a staggering \textbf{96%} success rate, exposing severe brittleness in memory-less defense. Furthermore, we reveal a \textbf{``Complexity Paradox''}: while complex, iteratively refined attacks are effective, they often trigger defensive compliance, whereas simple strategies achieve a higher rate of genuine persuasion (\textbf{84.7%}). Our code and dataset are available at GitHub, https://github.com/cza1006/llm-persuasion-defense.

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