Cover Image

Let's Measure Information Step-by-Step: AI-Based Evaluation Beyond Vibes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Robertson, Zachary, Koyejo, Sanmi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Information Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Measurement to Meaning: A Validity-Centered Framework for AI Evaluation
by: Salaudeen, Olawale, et al.
Published: (2025)

High-Dimensional Markov-switching Ordinary Differential Processes
by: Tsai, Katherine, et al.
Published: (2024)

Separable Computation of Information Measures
by: Xu, Xiangxiang, et al.
Published: (2025)

Measures of Information Reflect Memorization Patterns
by: Bansal, Rachit, et al.
Published: (2022)

Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks
by: Robertson, Zachary, et al.
Published: (2023)

Causal Entropy and Information Gain for Measuring Causal Control
by: Simoes, Francisco Nunes Ferreira Quialheiro, et al.
Published: (2023)

Information-Theoretic Measures on Lattices for High-Order Interactions
by: Liu, Zhaolu, et al.
Published: (2024)

Bounds on the Excess Minimum Risk via Generalized Information Divergence Measures
by: Omanwar, Ananya, et al.
Published: (2025)

Information-Theoretic Progress Measures reveal Grokking is an Emergent Phase Transition
by: Clauw, Kenzo, et al.
Published: (2024)

Understanding Encoder-Decoder Structures in Machine Learning Using Information Measures
by: Silva, Jorge F., et al.
Published: (2024)

Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection
by: Beck, Nathan, et al.
Published: (2024)

Causally Inspired Regularization Enables Domain General Representations
by: Salaudeen, Olawale, et al.
Published: (2024)

Rate-Distortion-Perception Tradeoff Based on the Conditional-Distribution Perception Measure
by: Salehkalaibar, Sadaf, et al.
Published: (2024)

Tighter Information-Theoretic Generalization Bounds via a Novel Class of Change of Measure Inequalities
by: Liu, Yanxiao, et al.
Published: (2026)

Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models
by: Reifert, Robert-Jeron, et al.
Published: (2026)

A Global Characterization of $f$-Divergences Yielding PSD Mutual-Information Matrices
by: Robertson, Zachary
Published: (2026)

Measuring the Intrinsic Dimension of Earth Representations
by: Rao, Arjun, et al.
Published: (2025)

Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements
by: Kızıldağ, Eren C.
Published: (2025)

Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors
by: Vahedifar, Mohammad Ali, et al.
Published: (2023)

AI/ML Life Cycle Management for Interoperable AI Native RAN
by: Huang, Chu-Hsiang, et al.
Published: (2025)

Beyond Point Estimates: Likelihood-Based Full-Posterior Wireless Localization
by: Lei, Haozhe, et al.
Published: (2025)

Pretraining Scaling Laws for Generative Evaluations of Language Models
by: Schaeffer, Rylan, et al.
Published: (2025)

Measuring the Predictability of Recommender Systems using Structural Complexity Metrics
by: Abeliuk, Andrés, et al.
Published: (2024)

VBO-MI: A Fully Gradient-Based Bayesian Optimization Framework Using Variational Mutual Information Estimation
by: Mirkarimi, Farhad
Published: (2026)

Beyond Fixed False Discovery Rates: Post-Hoc Conformal Selection with E-Variables
by: Zhu, Meiyi, et al.
Published: (2026)

Learning Capacity: A Measure of the Effective Dimensionality of a Model
by: Chen, Daiwei, et al.
Published: (2023)

Digital Twin-Assisted Measurement Design and Channel Statistics Prediction
by: Williams, Robin J., et al.
Published: (2026)

Exact Recovery of Sparse Binary Vectors from Generalized Linear Measurements
by: Mazumdar, Arya, et al.
Published: (2025)

Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications
by: Qin, Hai-Long, et al.
Published: (2025)

Welfare, Improvability, and Variance: A Principal-Agent Approach to Optimal Benchmark Item Aggregation
by: Haupt, Andreas, et al.
Published: (2026)

Uncertainty Quantification and Data Efficiency in AI: An Information-Theoretic Perspective
by: Simeone, Osvaldo, et al.
Published: (2025)

General Information Metrics for Improving AI Model Training Efficiency
by: Xu, Jianfeng, et al.
Published: (2025)

Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
by: Zhang, Kaihong, et al.
Published: (2024)

ZipNN: Lossless Compression for AI Models
by: Hershcovitch, Moshik, et al.
Published: (2024)

Probing the Information Theoretical Roots of Spatial Dependence Measures
by: Wang, Zhangyu, et al.
Published: (2024)

LightThinker: Thinking Step-by-Step Compression
by: Zhang, Jintian, et al.
Published: (2025)

Directed Information $γ$-covering: An Information-Theoretic Framework for Context Engineering
by: Huang, Hai
Published: (2025)

Post-Selection Distributional Model Evaluation
by: Farzaneh, Amirmohammad, et al.
Published: (2026)

In-Context Learning of Energy Functions
by: Schaeffer, Rylan, et al.
Published: (2024)

The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements
by: Chaabouni, Youssef, et al.
Published: (2025)