LLM Refusal Behavior

LLM: Large Language Model

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1 paper in the last four weeks, down 86% on the four weeks before. 0.0% of all new papers.

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EmoRSS: Mitigating Emotion-Induced Over-Refusal in Large Language Models
Oct 4, 2026Shuyi Miao, Yaojin Ma, Chenhang Cui +5LLM Alignment LLM Refusal Behavior
Beihang University · University of Science and Technology Beijing · National University of Singapore +2
Mitigating LLM Over-Refusal via Dynamic Semantic Routing Calibration
Sep 6, 2026Zixuan Wang, Bingjie Zhang, He Zhao +1Mechanistic Interpretability LLM Refusal Behavior
School of Artificial Intelligence, Jilin University · CSIRO, Australia · Center of Excellence for Generative AI, King Abdullah University of Science and Technology
PACE: Towards Surfacing Hidden Conflicts in User Requests
Sep 3, 2026Yoojin Kim, Jihyoung Jang, Hyounghun KimAI Agent Safety LLM Refusal Behavior
Department of Computer Science and Engineering, POSTECH · Graduate School of Artificial Intelligence, POSTECH · Department of Computer Science
Door-in-the-Face Requests and Refusal Behaviour in Large Language Models
Sep 2, 2026Til JordanPersuasion in Language Models LLM Refusal Behavior
A Unified Mechanistic Analysis of Knowledge- and Safety-Based Refusals
Sep 1, 2026Yuri Son, Seunghee Kim, Hyuhng Joon Kim +1LLM Interpretability LLM Refusal Behavior
1Hanyang University · 2Samsung Electronics
Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts
Sep 1, 2026Rui Yang, Yang Hong, Yichao Xu +3LLM Safety Benchmarks LLM Refusal Behavior
Johns Hopkins University
You Shouldn't Have Asked: A Pragmatics-Inspired Taxonomy for Evaluating LLM Refusals
Aug 31, 2026Ruoxuan Li, Pinqiao Wang, Sheng Li +1Language Model Safety Evaluation Pragmatic Reasoning in Language Models
Stony Brook University · University of Virginia
Refusing Intent, Not Form: Wrapper-Based Intent-Group Supervision for LLM Safety
Aug 13, 2026Ping Wu, Haibo Tong, Feifei Zhao +7LLM Safety Alignment LLM Refusal Behavior
BrainCog Lab, Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · Beijing Key Laboratory of Safe AI and Superalignment +2
A Constitution-Grid Instrument for Data-Efficient RL Alignment (C-Guard)
Jul 31, 2026Xianling ZhangMulti-Objective Reinforcement Learning LLM Safety Alignment
Independent Researcher
Refusal-Gated Decoding: Preserving Refusal Behavior Under High-Temperature Sampling
Jul 22, 2026Phillip Howard, Xin Su, Allen Roush +3Language Model Decoding LLM Refusal Behavior
Thoughtworks
Adaptive Capitulation: A Structural Failure Mode of LLM Responses in Vulnerability Contexts
Jul 21, 2026Eunna LeeLanguage Model Safety Evaluation LLM Refusal Behavior
Independent Researcher
Abliteration Is Not a Scalpel: Off-Target Effects of Refusal Removal on Decision Disposition Across Model Families
Jul 19, 2026Aleksander FafułaLLM Auditing LLM Refusal Behavior
independent researcher • funduszai.pl
The Refusal Residue: When Probes Catch Alignment Faking and When They Don't
Jul 15, 2026Aman MehtaLLM Auditing Deception in Language Models
Snowflake AI Research
Capabilities of Claude Fable 5 on Biomedical Challenge Problems
Jul 12, 2026Dominic Okonkwo, Magnus Hodgson, Temitope I. David +1Biomedical QA LLM Refusal Behavior
School of Computing, University of Georgia · Department of Chemistry, University of Illinois · Institute of Bioinformatics, University of Georgia
Evaluating calibrated refusal and safe usefulness in dual-use biology settings
Jul 6, 2026Edwin H. Wintermute, Harmon Bhasin, Christina M. Agapakis +13LLM Refusal Behavior Safety Filtering
American Wetware, Boston, MA · LatchBio, San Francisco, CA
Whose Side Is Your Agent On? Multi-Party Principal Loyalty in LLM Agents
Jun 29, 2026Bojie Li, Noah ShiLLM Agent Evaluation LLM Refusal Behavior
Pine AI · University of Washington
Refusal Lives Downstream of Persona in Chat Models
Jun 24, 2026Viola Zhong, Qirui LiLanguage Model Steering LLM Refusal Behavior
Independent · Department of Mathematics Pohang University of Science and Technology
Do Thinking Tokens Help with Safety?
Jun 23, 2026Narutatsu Ri, Abhishek Panigrahi, Sanjeev AroraLLM Refusal Behavior LLM Safety Evaluation
Princeton Language and Intelligence, Princeton University
LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context
Jun 23, 2026Anastasiia Kucherenko, François Brouchoud, Dimitri Percia David +1LLM Prompting Small Language Models
IEM, HEG, HES-SO Valais-Wallis Sierre, Switzerland
The Geometry of Refusal: Linear Instability in Safety-Aligned LLMs
Jun 21, 2026Shivam Ratnakar, Kartikeya VatsLanguage Model Steering Adversarial Attacks on LLMs
University of Southern California · Independent Researcher
A Low-Rank Subspace Analysis of LLM Interventions
Jun 12, 2026Angira Sharma, Christian Schroeder de Witt, Philip Torr +2LLM Interpretability LLM Refusal Behavior
University of Oxford
LoMC: Localized Multidirectional Correction for Refusal Suppression in Routed Foundation Models
Jun 10, 2026Yan Hong, Kedong Xiu, Wei Li +6Mixture-of-Experts Language Models LLM Refusal Behavior
Ant Group · Zhejiang University · Shanghai Jiao Tong University
Quality Is Not a Safety Proxy Under Quantization
Jun 8, 2026Sahil KadadekarLLM Quantization LLM Refusal Behavior
Independent Researcher
PsychoSafe: Eliciting Psychologically-Informed Refusals in Large Language Models
Jun 8, 2026Gianluca Barmina, Federico Torrielli, Sven Harms +7Emotional Support Conversation Mental Health
University of Southern Denmark · University of Turin · University of Hamburg +1
Will the Agent Recuse Itself? Measuring LLM-Agent Compliance with In-Band Access-Deny Signals
Jun 4, 2026Thamilvendhan MunirathinamLLM Agent Evaluation LLM Refusal Behavior
(Mis)generalization of Helpful-only Fine-tuning
Jun 3, 2026Mohammad Omar Khursheed, Baram Sosis, Fabien RogerSupervised Fine-Tuning LLM Sycophancy
Anthropic Fellows Program MATS · Anthropic
Expert-Aware Refusal Steering
Jun 2, 2026Anna C. Marbut, Daniel R. Olson, Travis J. WheelerMixture-of-Experts Language Models Language Model Steering
Department of Interdisciplinary Studies University of Montana Missoula, MT, USA · Department of Pharmacy Practice & Science University of Arizona Tucson, AZ, USA · European Bioinformatics Institute European Molecular Biology Laboratory Wellcome Genome Campus, Hinxton, United Kingdom
DDOR: Delta Debugging for Explainable Overrefusal Testing and Repair
Jun 2, 2026Qinyan Zhou, Peixin Zhang, Jun Sun +2LLM Guardrails LLM Refusal Behavior
Southeast University, China · School of Computing and Information Systems, Singapore Management University, Singapore · Zhejiang University, China +1
A New Framework for Cybersecurity Refusals in AI Agents
May 31, 2026Eliot Krzysztof Jones, Mateusz Dziemian, Matt Fredrikson +1LLM Agent Evaluation LLM Refusal Behavior
Work done while at Gray Swan · Gray Swan AI · Carnegie Mellon University
BioRefusalAudit: Auditing Biosecurity Refusal Depth Using General and Domain-Fine-Tuned Sparse Autoencoders
May 28, 2026Caleb DeLeeuwLanguage Model Safety Evaluation Sparse Autoencoders
Independent researcher

Oct 4, 2026, cs.AIJ/K move · Enter open · S save

EmoRSS: Mitigating Emotion-Induced Over-Refusal in Large Language Models

Shuyi Miao, Yaojin Ma, Chenhang Cui, Xiaohao Liu+4

Beihang University · University of Science and Technology Beijing · National University of Singapore+2

LLM Alignment LLM Refusal Behavior Over-Refusal Activation Steering

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Emotional expression can influence the safety decisions of large language models (LLMs), offering a potential avenue for improving safety alignment. Existing studies have mainly focused on how emotional expressions facilitate attacks under harmful requests, while overlooking their effects on benign requests. We find that emotional expression can also systematically increase refusal tendencies on benign requests, leading to unnecessary over-refusal. Based on this observation, we propose emotion-guided refusal subspace steering (EmoRSS), an activation-steering method that mitigates emotion-induced over-refusal while preserving refusal behaviour on harmful requests. Specifically, we first identify a refusal-sensitive layer using layer-wise linear probes and construct a refusal subspace from sparse autoencoder (SAE) features aligned with the probe direction. Next, we use paired regular and emotional requests with the same queries to estimate the mean activation shift in the features defining the refusal subspace. Finally, we decode this shift into an activation intervention vector and apply it in the reverse refusal direction during inference, without updating the backbone parameters. Experiments on two LLMs show that, when requests contain emotional expressions, our method achieves a more favourable trade-off between refusing harmful requests and answering benign ones than prior over-refusal mitigation baselines, while better preserving general task performance.

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