Transformer Interpretability

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Concepts Whisper While Syntax Shouts: Spectral Anti-Concentration and the Dual Geometry of Transformer Representations
May 2, 2026Pratyush Acharya, Nuraj Rimal, Habish DhakalTransformer Interpretability Representation Learning
Beyond Decodability: Reconstructing Language Model Representations with an Encoding Probe
May 1, 2026Gaofei Shen, Martijn Bentum, Tomas O. Lentz +2Transformer Interpretability Representation Probing
Tilburg University · Radboud University
AttriBE: Quantifying Attribute Expressivity in Body Embeddings for Recognition and Identification
Apr 29, 2026Basudha Pal, Siyuan Huang, Anirudh Nanduri +2Transformer Interpretability Representation Probing
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218 USA · Department of Electrical and Computer Engineering, University of Maryland, College Park, MD 20742 USA · Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218 USA +1
Efficient and Interpretable Transformer for Counterfactual Fairness
Apr 29, 2026Panyi Dong, Zhiyu QuanTransformer Interpretability Transformer
Acturial and Risk Mangament Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, USA.
Architecture Determines Observability of Transformers
Apr 27, 2026Thomas CarmichaelTransformer Interpretability Language Model Error Detection
Independent Researcher
Rank, Head-Channel Non-Identifiability, and Symmetry Breaking: A Precise Analysis of Representational Collapse in Transformers
Apr 26, 2026Giansalvo CirrincioneTransformer Interpretability Representation Collapse
aLaboratoire LTI, Université de Picardie Jules Verne, Chemin du Thil, 80025 Amiens, France
Applications of the Transformer Architecture in AI-Assisted English Reading Comprehension
Apr 26, 2026Ping LiTransformer Interpretability Social Bias in Language Models
a Shandong Management University, Jinan, Shandong Province, 250357, China
Supernodes and Halos: Loss-Critical Hubs in LLM Feed-Forward Layers
Apr 26, 2026Audrey Cherilyn, Houman SafaaiTransformer Interpretability LLM Pruning
Kempner Institute at Harvard University
From Edges to Depth: Probing the Spatial Hierarchy in Vision Transformers
Apr 25, 2026Jainum SanghaviTransformer Interpretability Visual Spatial Reasoning
Northeastern University
When Chain-of-Thought Fails, the Solution Hides in the Hidden States
Apr 25, 2026Houman Mehrafarin, Amit Parekh, Ioannis KonstasTransformer Interpretability CoT Reasoning
Heriot-Watt University, Edinburgh, United Kingdom · University of Edinburgh, Edinburgh, United Kingdom
Real-Time AttentionBender: Granular Interactive Network Bending of Video Diffusion Transformers
Apr 24, 2026Adam Cole, Rebecca Fiebrink, Mick GriersonTransformer Interpretability Video Diffusion Models
Creative Computing Institute University of the Arts London London, UK
Dissociating Decodability and Causal Use in Bracket-Sequence Transformers
Apr 24, 2026Aryan Sharma, Cutter Dawes, Shivam RavalTransformer Interpretability Self-Attention
1Yale University · 2Independent · 3Harvard University
Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2
Apr 23, 2026Isabel Kurth, Paulo Yanez Sarmiento, Bernhard Y. RenardTransformer Interpretability Attention Mechanisms
Hasso Plattner Institute University of Potsdam
AttentionBender: Manipulating Cross-Attention in Video Diffusion Transformers as a Creative Probe
Apr 22, 2026Adam Cole, Mick GriersonTransformer Interpretability Video Diffusion Models
University of the Arts London London, UK
Cognitive Alignment At No Cost: Inducing Human Attention Biases For Interpretable Vision Transformers
Apr 21, 2026Ethan KnightsTransformer Interpretability Visual Attention
Cambridge, UK
Decision-Aware Attention Propagation for Vision Transformer Explainability
Apr 20, 2026Sehyeong Jo, Gangjae Jang, Haesol ParkTransformer Interpretability Vision Transformer
Aarhus University · University of Colorado Boulder · KIST
One Mask to Rule Them All: On Hidden Facts after Editing and How to Find Them
Apr 18, 2026Ali Holmov, Paul Youssef, Nandi Schoots +1Knowledge Editing Transformer Interpretability
Technical University of Munich · Marburg University · University of Oxford
Structural Instability of Feature Composition
Apr 18, 2026Yunpeng ZhouFeature Superposition Transformer Interpretability
Whiteknights House, Whiteknights, Reading, RG6 6UR
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
What Is the Minimum Architecture for Prolepsis? Early Irrevocable Commitment Across Tasks in Small Transformers
Apr 16, 2026Éric JacopinTransformer Interpretability Attention Head Analysis
Cosmic AI
Hallucination as Trajectory Commitment: Causal Evidence for Asymmetric Attractor Dynamics in Transformer Generation
Apr 16, 2026G. Aytug AkarlarTransformer Interpretability Hallucination in Language Models
Chimera Research Initiative Istanbul, Türkiye · Chimera Research Initiative is an independent research effort exploring causal and neuro-symbolic approaches to AI systems.
Relational Preference Encoding in Looped Transformer Internal States
Apr 10, 2026Jan KirinPairwise Preference Learning Reward Modeling
From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales
Mar 31, 2026Ivan Viakhirev, Kirill Borodin, Grach MkrtchianTransformer Interpretability Automatic Speech Recognition
Information Technologies, Mechanics and Optics University, Russia · lab260, Moscow Technical University of Communications and Informatics, Russia · BitmanagerAI, UAE
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.
Feature-level Interaction Explanations in Multimodal Transformers
Mar 4, 2026Yeji Kim, Housam Khalifa Bashier Babiker, Mi-Young Kim +1Transformer Interpretability Feature Attribution
University of Alberta, Edmonton, AB, Canada · University of Waikato, Hamilton, New Zealand · University of Alberta, Camrose, AB, Canada
MetaOthello: A Controlled Study of Multiple World Models in Transformers
Feb 26, 2026Aviral Chawla, Galen Hall, Juniper LovatoTransformer Interpretability World Model Learning
Vermont Complex Systems Institute, University of Vermont, Burlington, VT · University of Michigan, Ann Arbor, MI
Transformers converge to invariant algorithmic cores
Feb 26, 2026Joshua S. SchiffmanTransformer Interpretability Invariant Representation Learning
New York Genome Center, New York, NY, USA.
How Transformers Reject Wrong Answers: Rotational Dynamics of Factual Constraint Processing
Feb 25, 2026Javier MarínTransformer Interpretability LLM Interpretability
Groundlens-dev
Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms
Feb 9, 2026Nobuyuki OtaTransformer Interpretability Single-Cell Perturbation Modeling
Independent Researcher, Burlingame, CA, USA
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

May 2, 2026, cs.LGJ/K move · Enter open · S save

Concepts Whisper While Syntax Shouts: Spectral Anti-Concentration and the Dual Geometry of Transformer Representations

Pratyush Acharya, Nuraj Rimal, Habish Dhakal

Transformer Interpretability Representation Learning Neural Representation Geometry Cross-Lingual Representation Alignment Neural Encoding Cross-Lingual Transfer

Open paper AskPDF arXiv

We test whether the causal inner product of \citet{park2024linear} -- defined by the unembedding covariance

Σ

-- enables cross-lingual concept transport. Across 17 models and 4 language pairs, a matched-spectrum randomization test finds that Whitened Causal Alignment is indistinguishable from spectral regularization alone (

p = 0.95

). However, this failure reveals a broader phenomenon: anti-concentration is observed in residual-stream difference-of-means vectors across five architecture families (

p < 10^{-33}

) and supported by SAE features (e.g.,

p = 4.5 \times 10^{-19}

) and linear probes on Gemma and Llama. We discover a \emph{dual geometry}: activation-space concept directions anti-concentrate in the spectral tail, while static unembedding-row contrasts \emph{concentrate} in high-variance directions (

p < 10^{-4}

). Split-injection causal interventions support the functional basis on Gemma and Llama (Cohen's

d

up to

1.80

), and POS-tag probing across 8 models shows syntax preferentially encodes in the high-variance subspace in 6 of 8 architectures (

p < 0.013

), with the Qwen~2.5 family showing a significant reversal consistent with architecture-specific spectral structure. These results suggest transformers may rotate semantic content into spectrally quiet regions during contextualized processing, encoding concepts where they can be manipulated with reduced grammatical disruption.

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Latest papers 224