Imagen de Portada

What Representational Similarity Measures Imply about Decodable Information

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Harvey, Sarah E., Lipshutz, David, Williams, Alex H.
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective
por: Nielsen, Beatrix M. G., et al.
Publicado: (2025)

Molecular Graph Representation Learning via Structural Similarity Information
por: Yao, Chengyu, et al.
Publicado: (2024)

Logit Distance Bounds Representational Similarity
por: Nielsen, Beatrix M. G., et al.
Publicado: (2026)

Measuring the Measures: Discriminative Capacity of Representational Similarity Metrics Across Model Families
por: Wu, Jialin, et al.
Publicado: (2025)

Exploration Implies Data Augmentation: Reachability and Generalisation in Contextual MDPs
por: Weltevrede, Max, et al.
Publicado: (2024)

Discriminating image representations with principal distortions
por: Feather, Jenelle, et al.
Publicado: (2024)

A Methodological Framework for Measuring Spatial Labeling Similarity
por: Du, Yihang, et al.
Publicado: (2025)

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples
por: Vouitsis, Noël, et al.
Publicado: (2024)

Measuring Time-Series Dataset Similarity using Wasserstein Distance
por: Chen, Hongjie, et al.
Publicado: (2025)

SERE: Similarity-based Expert Re-routing for Efficient Batch Decoding in MoE Models
por: Wu, Juntong, et al.
Publicado: (2026)

How Data Augmentation Shapes Neural Representations
por: He, Tianxiao, et al.
Publicado: (2026)

What do Geometric Hallucination Detection Metrics Actually Measure?
por: Yeats, Eric, et al.
Publicado: (2026)

Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
por: Ibrahim, Mark, et al.
Publicado: (2024)

Measuring What AI Systems Might Do: Towards A Measurement Science in AI
por: Voudouris, Konstantinos, et al.
Publicado: (2026)

The Triangle of Similarity: A Multi-Faceted Framework for Comparing Neural Network Representations
por: Sirikova, Olha, et al.
Publicado: (2026)

What Do Learned Models Measure?
por: Žliobaitė, Indrė
Publicado: (2026)

What Drives Representation Steering? A Mechanistic Case Study on Steering Refusal
por: Cheng, Stephen, et al.
Publicado: (2026)

From Molecules to Mixtures: Learning Representations of Olfactory Mixture Similarity using Inductive Biases
por: Tom, Gary, et al.
Publicado: (2025)

Measuring Orthogonality in Representations of Generative Models
por: Geyer, Robin C., et al.
Publicado: (2024)

Measuring What Matters: Intrinsic Distance Preservation as a Robust Metric for Embedding Quality
por: Hart, Steven N., et al.
Publicado: (2024)

STree: Speculative Tree Decoding for Hybrid State-Space Models
por: Wu, Yangchao, et al.
Publicado: (2025)

What is causal about causal models and representations?
por: Jørgensen, Frederik Hytting, et al.
Publicado: (2025)

Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding
por: Liu, Guangyi, et al.
Publicado: (2024)

An Explainable Multi-Task Similarity Measure: Integrating Accumulated Local Effects and Weighted Fréchet Distance
por: Hidalgo, Pablo, et al.
Publicado: (2026)

Early Detection of Multidrug Resistance Using Multivariate Time Series Analysis and Interpretable Patient-Similarity Representations
por: Escudero-Arnanz, Óscar, et al.
Publicado: (2025)

Position: What Can Large Language Models Tell Us about Time Series Analysis
por: Jin, Ming, et al.
Publicado: (2024)

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning
por: Hong, Guan Zhe, et al.
Publicado: (2024)

What Radio Waves Tell Us about Sleep
por: He, Hao, et al.
Publicado: (2024)

Learning Human-Aligned Representations with Contrastive Learning and Generative Similarity
por: Marjieh, Raja, et al.
Publicado: (2024)

A Clustering Method with Graph Maximum Decoding Information
por: Xu, Xinrun, et al.
Publicado: (2024)

Comparing noisy neural population dynamics using optimal transport distances
por: Nejatbakhsh, Amin, et al.
Publicado: (2024)

VeTraSS: Vehicle Trajectory Similarity Search Through Graph Modeling and Representation Learning
por: Cheng, Ming, et al.
Publicado: (2024)

Comprehensive Description of Uncertainty in Measurement for Representation and Propagation with Scalable Precision
por: Darijani, Ali, et al.
Publicado: (2026)

Measuring Leakage in Concept-Based Methods: An Information Theoretic Approach
por: Makonnen, Mikael, et al.
Publicado: (2025)

Similarity as Reward Alignment: Robust and Versatile Preference-based Reinforcement Learning
por: Rajaram, Sara, et al.
Publicado: (2025)

Perceptual Similarity for Measuring Decision-Making Style and Policy Diversity in Games
por: Lin, Chiu-Chou, et al.
Publicado: (2024)

RESTAD: REconstruction and Similarity based Transformer for time series Anomaly Detection
por: Ghorbani, Ramin, et al.
Publicado: (2024)

Convergent Evolution: How Different Language Models Learn Similar Number Representations
por: Fu, Deqing, et al.
Publicado: (2026)

Measure-Theoretic Anti-Causal Representation Learning
por: Behnam, Arman, et al.
Publicado: (2025)

Bias Similarity Measurement: A Black-Box Audit of Fairness Across LLMs
por: Jeong, Hyejun, et al.
Publicado: (2024)