LLM Interpretability

LLM: Large Language Model

Follow this topic Ask about this topic

Momentum

57 papers in the last four weeks, up 73% on the four weeks before. 0.6% of all new papers.

Jul 13Week of Sep 28

Latest papers 546

All topics

Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering
Apr 19, 2026Li Zheng, Xin Zhang, Shuyi He +5Language Model Steering LLM Interpretability
Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China · Ant International · School of Computing Technologies, RMIT University, Australia
AtManRL: Towards Faithful Reasoning via Differentiable Attention Saliency
Apr 17, 2026Max Henning Höth, Kristian Kersting, Björn Deiseroth +1CoT Faithfulness Feature Attribution
Aleph Alpha Research Lab1141 · TU Darmstadt Hessian.AI
Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures
Apr 17, 2026Yutong Gao, Qinglin Meng, Yuan Zhou +1Transformer Interpretability LLM Interpretability
MOE Key Lab of Computational Linguistics, Peking University · Nanjing University of Science and Technology · Purdue University +1
Disentangling Mathematical Reasoning in LLMs: A Methodological Investigation of Internal Mechanisms
Apr 17, 2026Tanja Baeumel, Josef van Genabith, Simon OstermannLLM Interpretability Mechanistic Interpretability
German Research Center for Artificial Intelligence (DFKI) · Saarland University · Center for European Research in Trusted AI (CERTAIN)
LLM Reasoning Is Latent, Not the Chain of Thought
Apr 17, 2026Wenshuo WangLLM Interpretability CoT Reasoning
School of Future Technology, South China University of Technology, China
LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance
Apr 16, 2026Jack Wei Lun Shi, Minghao Dang, Wawan Solihin +1Feature Attribution LLM Interpretability
Department of Civil and Environmental Engineering, National University of Singapore, 117576, Singapore · School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China · Research and Innovation, NovaCITYNETS Pte.Ltd., 348615, Singapore
LLMbench: A Comparative Close Reading Workbench for Large Language Models
Apr 16, 2026David M. BerryLLM Evaluation LLM Interpretability
University of Sussex
Mechanistic Decoding of Cognitive Constructs in Large Language Models
Apr 16, 2026Yitong Shou, Manhao GuanLLM Interpretability Causal Interventions in Language Models
Zhejiang University, Hangzhou 310027, China. · The authors are with the College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China.
Robust Explanations for User Trust in Enterprise NLP Systems
Apr 13, 2026Guilin Zhang, Kai Zhao, Jeffrey Friedman +3Explainable Artificial Intelligence LLM Interpretability
Workday AI Research
What Drives Representation Steering? A Mechanistic Case Study on Steering Refusal
Apr 9, 2026Stephen Cheng, Sarah Wiegreffe, Dinesh ManochaLanguage Model Steering LLM Interpretability
University of Maryland, College Park
What are They Thinking? Delineation, Probing, and Tracking of Concepts in LLMs
Apr 7, 2026Mohamed Abdelwahab, Michelle Yu Collins, Sihan Chen +5Linear Probing LLM Interpretability
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto
How Alignment Routes: Localizing, Scaling, and Controlling Policy Circuits in Language Models
Apr 6, 2026Gregory N. FrankLLM Interpretability LLM Safety
Chief Scientist, Molt AI Corp.
GRADE: Probing Knowledge Gaps in LLMs through Gradient Subspace Dynamics
Apr 3, 2026Yujing Wang, Yuanbang Liang, Yukun Lai +2LLM Interpretability LLM Uncertainty Estimation
Beihang University · Cardiff University · King’s College London
Over-Refusal and Representation Subspaces: A Mechanistic Analysis of Task-Conditioned Refusal in Aligned LLMs
Mar 29, 2026Utsav Maskey, Mark Dras, Usman NaseemLLM Interpretability LLM Refusal Behavior
Macquarie University
From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents
Mar 27, 2026Trilok Padhi, Ramneet Kaur, Krishiv Agarwal +9LLM Interpretability Representation Probing
Georgia State University, Atlanta, USA · Computer Science Lab, SRI, Menlo Park, USA · Computer Science Department, University of Florida, USA +1
Perturbation: A simple and efficient adversarial tracer for representation learning in language models
Mar 25, 2026Joshua Rozner, Cory ShainRepresentation Learning LLM Interpretability
Stanford University
INTRYGUE: Induction-Aware Entropy Gating for Reliable RAG Uncertainty Estimation
Mar 23, 2026Alexandra Kuleshova, Andrei Volodichev, Daria Kotova +1Hallucination Detection LLM Interpretability
Applied AI Institute
Dual Path Attribution: Efficient Attribution for SwiGLU-Transformers through Layer-Wise Target Propagation
Mar 20, 2026Lasse Marten Jantsch, Dong-Jae Koh, Seonghyeon Lee +1Transformer Interpretability LLM Interpretability
Department of Computer Science and Engineering, Kyungpook National University, Daegu, Korea.
ICE: Intervention-Consistent Explanation Evaluation with Statistical Grounding for LLMs
Mar 19, 2026Abhinaba Basu, Pavan ChakrabortyExplanation Evaluation LLM Interpretability
1Indian Institute of Information Technology, Allahabad (IIITA) · 2National Institute of Electronics and Information Technology (NIELIT)
Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability
Mar 16, 2026Fan Huang, Haewoon Kwak, Jisun AnMoral Reasoning in Language Models LLM Interpretability
Indiana University Bloomington / United States
Causal Tracing of Audio-Text Fusion in Large Audio Language Models
Mar 14, 2026Wei-Chih Chen, Chien-yu Huang, Hung-yi LeeLLM Interpretability Audio Understanding
National Taiwan University, Taiwan · Carnegie Mellon University, United States
World Properties without World Models: Distributional Associations and the Interpretation of Decoding Results from Language Models
Mar 4, 2026Elan BarenholtzLLM World Models Word Embeddings
Department of Psychology & Center for Complex Systems and Brain Sciences Florida Atlantic University
Step-Level Sparse Autoencoder for Reasoning Process Interpretation
Mar 3, 2026Xuan Yang, Jiayu Liu, Yuhang Lai +3LLM Interpretability Sparse Autoencoders
Department of Data Science, City University of Hong Kong · Hong Kong Institute of AI for Science, City University of Hong Kong · Li Auto Inc +1
The GRADIEND Python Package: An End-to-End System for Gradient-Based Feature Learning
Feb 27, 2026Jonathan Drechsel, Steffen HerboldLLM Interpretability Language Modeling
Faculty of Computer Science and Mathematics University of Passau
Probing for Knowledge Attribution in Large Language Models
Feb 26, 2026Ivo Brink, Alexander Boer, Dennis UlmerLLM Interpretability Hallucination in Language Models
KPMG NL / University of Amsterdam Amsterdam, The Netherlands · KPMG NL Amsterdam, The Netherlands · University of Amsterdam Amsterdam, The Netherlands
How Transformers Reject Wrong Answers: Rotational Dynamics of Factual Constraint Processing
Feb 25, 2026Javier MarínTransformer Interpretability LLM Interpretability
Groundlens-dev
Compressed Sensing for Capability Localization in Large Language Models
Feb 11, 2026Anna Bair, Yixuan Even Xu, Mingjie Sun +1Attention Head Analysis LLM Interpretability
Carnegie Mellon University
Patches of Nonlinearity: Instruction Vectors in Large Language Models
Feb 8, 2026Irina Bigoulaeva, Jonas Rohweder, Subhabrata Dutta +1Transformer Interpretability LLM Interpretability
Ubiquitous Knowledge Processing Lab (UKP Lab) · Department of Computer Science, Technical University of Darmstadt · National Research Center for Applied Cybersecurity ATHENE, Germany
CoT is Not the Chain of Truth: An Empirical Internal Analysis of Reasoning LLMs for Fake News Generation
Feb 4, 2026Zhao Tong, Chunlin Gong, Yiping Zhang +5Language Model Safety Evaluation LLM Interpretability
Institute of Information Engineering, Chinese Academy of Sciences · School of Cyber Security, University of Chinese Academy of Sciences · Shanghai AI Laboratory +3
A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior
Feb 2, 2026Harry Mayne, Justin Singh Kang, Dewi Gould +3Faithfulness of Language Model Explanations LLM Interpretability
University of Oxford · University of California, Berkeley · Independent +2

Apr 19, 2026, cs.CLJ/K move · Enter open · S save

Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering

Li Zheng, Xin Zhang, Shuyi He, Fei Li+4

Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan, China · Ant International · School of Computing Technologies, RMIT University, Australia

Language Model Steering LLM Interpretability Causal Interventions in Language Models

Open paper AskPDF arXiv

Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models (LLMs). Existing studies mostly rely on external optimizations, lacking in-depth exploration of internal representation mechanisms, thus failing to achieve fine-grained steering at the neuron level. A handful of works on neurons are confined to emotions, neglecting rhetoric neurons and their intrinsic connections. Traditional neuron masking also exhibits counterintuitive phenomena, making reliable verification of neuron functionality infeasible. To address these issues, we systematically investigate the neurons representation mechanisms and inherent associations of 6 emotion categories and 4 core rhetorical devices. We propose a neuron identification framework that integrates multi-dimensional screening, and design an adaptive masking method incorporating dynamic filtering, attenuation masking, and feedback optimization, enabling reliable causal validation of neuron functionality.Through neuron regulation, we achieve directed induction of non-target sentences and enhancement of emotion tasks via rhetoric neurons. Experiments on 5 commonly used datasets validate the effectiveness of our method, providing a novel paradigm for the fine-grained steering of emotion and rhetoric expressions in LLMs.

Momentum

Related topics

Latest papers 546