Representational Similarity Analysis

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2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Classical Hardness of Learning Functions of Hamiltonians
Oct 1, 2026Sota Hashimoto, Akinori KawachiQuantum Learning Quantum Machine Learning
Graduate School of Engineering, Mie University
What Converges in the Platonic Representation Hypothesis? Structure over Geometry
Sep 23, 2026Junwon You, Mihyun Jang, Sangwoo Mo +1Representational Similarity Analysis Convergence
KAIST · POSTECH
Different representation learning objectives recover distinct latent structures from the same psychometric data
Aug 31, 2026Cong Cao, Tassos C. Kyriakides, Pambos VrasidasPsychometric Properties Representational Similarity Analysis
Department of Biostatistics, Yale School of Public Health, Yale University, New Haven · Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, USA · Center for the Advancement of Research & Development in Educational Technology (CARDET), Nicosia, Cyprus
IRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers
Aug 5, 2026Vaishnavi B Mohan, Vijayakrishna Naganoor, Yashas Annadani +1Vision Transformer Visual Perception
University of Washington, USA · Microsoft, USA · TU Munich, Germany +1
Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective
Jul 30, 2026Rishabh Iyer, Truong Pham, Anay MajeeMutual Information Representational Similarity Analysis
The University of Texas at Dallas, Richardson, TX, USA · Adobe, San Jose, CA, USA
Lost in Visual Translation: A VLM-Assisted Perceptual-Semantic Coherence Framework for EEG-to-Image Reconstruction
Jul 14, 2026Sukriti Tiwari, BHVSP Subrahmanyam, Nidhi Goyal +1Representational Similarity Analysis Visual Fidelity
Department of Computer Science and Engineering, Mahindra University, Hyderabad, India · MU-VT Interdisciplinary Advanced Research Centre for Transformative Technologies, Mahindra University, Hyderabad, India · Avyakt Ehsaas
Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval
Jul 6, 2026Suhyeong Park, Junha Jung, Jungwoo Park +1Long Visual-Token Sequences Representational Similarity Analysis
The Catholic University of Korea · AIGEN Sciences Inc. · Korea University
Transformer Geometry Observatory TGO-II: Representational Similarity Observatory
Jul 2, 2026Kaustubh Kapil, Kishor P. UplaVision Transformer Representational Similarity Analysis
Department of Electronics Engineering Sardar Vallabhai National Institute of Technology (SVNIT), Surat, India
Do LLM Embedding Spaces Recover Expert Structure?
Jun 22, 2026Yixuan Zhu, Zhenke Duan, Fanghen LiMental Health Expert Demonstrations
Zhongnan University of Economics and Law
Scalable and Interpretable Representation Alignment with Ordinal Similarity
Jun 15, 2026Diogo Soares, Pankhil Gawade, Andrea Dittadi +1Representational Similarity Analysis Similarity and Metrics
Institute of AI for Health, Helmholtz Munich · School of Computation, Information and Technology, Technical University of Munich · Faculty of Mathematics, Informatics and Mechanics, University of Warsaw
A Unifying Framework for Concept-Based Representational Similarity
Jun 8, 2026Grégoire Dhimoïla, Victor Boutin, Agustin Martin Picard +2Representational Similarity Analysis Unified Framework
Brown University · ENS Paris Saclay · CNRS +2
Symmetric Divergence and Normalized Similarity: A Unified Topological Framework for Representation Analysis
Jun 4, 2026Yan Wang, Tianyang HuTopology Representational Similarity Analysis
School of Data Science The Chinese University of Hong Kong, Shenzhen
ReSAGE-PAR: Representational Similarity Assessment for Generative Expansion in Pedestrian Attribute Recognition
Jun 4, 2026Pablo Ayuso-Albizu, Pablo Carballeira, Juan C. SanMiguel +1Pedestrian Detection Large-Scale Image Datasets
Universidad Aut´onoma de Madrid, Madrid, Spain
Emergent Ordinal Geometry in Transformers Trained on Local Comparisons
May 31, 2026Nishit SinghRepresentational Similarity Analysis Transformer Architectures
Birla Institute of Technology and Science, Pilani India
Detection vs. Execution: Single-Bucket Probes Miss Half the Mamba-2 State Sink
May 30, 2026Yuhang JiangAblation Distributional Signatures
Independent Researcher
Supervised Training Rapidly Degrades Early Visual Cortex Alignment Across Biologically Plausible Learning Rules
May 28, 2026Nils LeuteneggerHuman Visual Cortex Representational Similarity Analysis
Independent Researcher, Switzerland
Similarity-based representation factorization for revealing interpretable dimensions in representational data
May 26, 2026Florian P. Mahner, Ka Chun Lam, Francisco Pereira +1Representational Similarity Analysis Exploratory Factor Analysis
Max Planck Institute for Human Cognitive and Brain Sciences · National Institute of Mental Health · Justus Liebig University Giessen +1
Cross-Species RSA Reveals Conserved Early Visual Alignment but Divergent Higher-Area Rankings Across Human fMRI and Macaque Electrophysiology
May 21, 2026Nils LeuteneggerHuman Visual Cortex Representational Similarity Analysis
Independent Researcher, Switzerland
Stimulus symmetries can confound representational similarity analyses
May 20, 2026Farhad Pashakhanloo, Jacob A. Zavatone-VethRepresentational Similarity Analysis Symmetry
Center for Brain Science and 2Society of Fellows Harvard University, Cambridge, MA, USA
Characterizing Universal Object Representations Across Vision Models
May 13, 2026Florian P. Mahner, Johannes Roth, Ka Chun Lam +3Representational Similarity Analysis Vision Foundation Models
Vision and Computational Cognition Group Max Planck Institute Justus-Liebig-University Giessen · Machine Learning Core National Institute of Mental Health Bethesda, MD, USA · Department of Cognitive Science Johns Hopkins University Baltimore, MD, USA
Extremely coarse learning objectives induce human-aligned representations in AI vision models
May 7, 2026Yash Mehta, Michael F. BonnerRepresentational Similarity Analysis Feedback
Department of Cognitive Science, Johns Hopkins University
Neuroscience-Inspired Analyses of Visual Interestingness in Multimodal Transformers
May 5, 2026Mathis Immertreu, Fitim Abdullahu, Thomas Kinfe +3Transformer Attention Detection Transformer
Cognitive Computational Neuroscience Group, Patter Recognition Lab, University Erlangen-Nürnberg, Germany · IDS Institut für Data Science, ZHAW School of Engineering, Winterthur, Switzerland · Mannheim Center for Neuromodulation and Neuroprosthetics, University Hospital Mannheim, Heidelberg University, Germany +3
Beyond Activation Alignment: The Geometry of Neural Sensitivity
May 4, 2026Amirhossein Yavari, Farnaz Zamani EsfahlaniRepresentational Similarity Analysis Subspace
Stephenson School of Biomedical Engineering, University of Oklahoma · Data Science and Analytics Institute, University of Oklahoma
Untrained CNNs Match Backpropagation at V1: A Systematic RSA Comparison of Four Learning Rules Against Human fMRI
Apr 18, 2026Nils LeuteneggerHuman Visual Cortex Representational Similarity Analysis
Independent Researcher, Switzerland
Similarity of Neural Network Representations in Superposition
Mar 31, 2026Sunny Liu, Habon Issa, André Longon +4Representational Similarity Analysis Neural Network Representations
Cold Spring Harbor Laboratory · UC San Diego · Anthropic +2
Logit Distance Bounds Representational Similarity
Feb 17, 2026Beatrix M. G. Nielsen, Emanuele Marconato, Luigi Gresele +2Kullback-Leibler Divergence Logit Lens
IT University of Copenhagen, Denmark · University of Trento, Italy · University of Copenhagen, Denmark +2
Revisiting the Platonic Representation Hypothesis: An Aristotelian View
Feb 16, 2026Fabian Gröger, Shuo Wen, Maria BrbićRepresentational Similarity Analysis Hypothesis
1EPFL · University of Basel · 3HSLU
Geometric Stability: The Missing Axis of Representations
Jan 14, 2026Prashant C. RajuRepresentational Similarity Analysis Geometric Machine Learning

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Classical Hardness of Learning Functions of Hamiltonians

Sota Hashimoto, Akinori Kawachi

Graduate School of Engineering, Mie University

Quantum Learning Quantum Machine Learning Np-Hard Hamiltonian Hard Hessian+1

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Morohoshi, Nakayama, Manabe, and Mitarai proposed a physically motivated quantum machine learning problem in which the goal is to predict quantities of the form

\operatorname{Tr}[f(H)ρ]

from classical descriptions of a Hamiltonian

H

and a quantum state

ρ

, where

f

is an unknown function. We call this problem Hamiltonian function learning in this paper. They constructed an efficient quantum learning algorithm under suitable conditions, while leaving a rigorous proof of average-case classical hardness open. In this paper, we rigorously prove the average-case classical hardness for two distribution-specific Hamiltonian function learning problems for

f_{\cos,π}(λ)=\cos(πλ)

and

f_{\exp,β}(λ)=e^{-βλ}

discussed in the paper of Morohoshi et al. under the assumption of the average-case hardness of factoring random RSA moduli. More specifically, we show that an efficient classical randomized learner under squared loss whose output hypotheses are evaluable in classical polynomial time for either problem would yield a classical randomized polynomial-time algorithm for factoring random RSA moduli.

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