Theory & Algorithms · Computer Science & AI
Information Theory
The newest papers in Information Theory that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
474 papers, from 4 September 2026 to 5 November 2026: 474 arXiv preprints.
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Newest papers, page 11
Multiple Importance Sampling for Guided Speculative Inference
We study an extension of the Guided Speculative Inference (GSI) algorithm for test-time-scaling of large language models (LLMs) to a novel setting where an ensemble of smaller LLMs proposes draft…One-shot entanglement generation and distillation via Petz recovery and binary hypothesis testing
How much entanglement can two distant laboratories share when their connection is noisy?SILMARILS-MV: Information-Theoretically Secure Multi-Verifier Signatures with Dealer-Free Key Issuance and Linear Aggregation for Permissioned Blockchains
Permissioned blockchains authenticate transactions, votes and quorum certificates with computationally secure signatures, and post-quantum replacements inflate consensus traffic by orders of…Temporal Degeneracy Limits Message Passing Decoding of QLDPC Codes Under Repeated Noisy Syndrome Measurements
Practical quantum computations can require logical error rates of $10^{-12}$ or lower.PQ-Vault: Provably Quantum-Safe Asset Custody for Unmodified Ethereum
A quantum computer could recover the key of any Ethereum account whose public key appears on chain.Generalization Bounds via Vector-Valued $L_p$ Correlation $V_α$
Understanding generalization of randomized learning algorithms remains a central challenge.Recursive Code Evolution for Task-Oriented Semantic Communications
Semantic communication jointly optimizes inference accuracy, channel use, and computation, yet the underlying communication program is typically specified before training.Quantum f-divergences from retrodictive tests: a unifying classical variational principle
The same classical f-divergence admits inequivalent extensions to quantum states.Asymmetric Likelihood-Free Hypothesis Testing
In likelihood-free hypothesis testing (LFHT), given samples from two unknown distributions $P,Q$ on $[n]$ with $\mathrm{d_{TV}}(P,Q)\geq\varepsilon$, and from a third distribution $D\in\{P,Q\}$, the…Minimax Optimality of the NPMLE for Gaussian Mixtures in Hellinger Distance
We analyze the problem of estimating univariate Gaussian mixture densities using the nonparametric maximum likelihood estimator (NPMLE) based on $n$ independent and identically distributed samples.Differentially Private Synthetic Data via Generalized Moment Matching
We study $(\varepsilon,δ)$-differentially private synthetic data for arbitrary databases of $n$ records in $[-1,1]^d$ under a specified integral probability metric (IPM).On the Adversarial Vulnerability of Neural Receivers with Unrolled LDPC Decoders
Neural receivers for 5G New Radio (NR) match classical model-based receivers in link-level performance, but their robustness to adversarial perturbations at the receiver input remains underexplored.Bayesian Fixed-Confidence Best-Arm Identification with Abstention
We study the Bayesian fixed-confidence best-arm identification problem in which a learner can abstain from making a terminal recommendation.Optimal Multitask Representations Under a Rate Constraint: An Information Bottleneck Analysis
Which pretraining objective yields the best representation for downstream tasks under an information budget?Certified Adaptive List Decoding for Error-Correcting Codes
Maximum-likelihood (ML) decoding of linear block codes is NP-hard, so neural decoders are evaluated by how closely they approach it.Certified Non-Degenerate Maximum-Likelihood Benchmarking of Quantum LDPC Decoders
The measured logical error rate of a quantum low-density parity-check (QLDPC) code depends on the decoding algorithm.Claims of emergence in AI should be grounded in information decomposition
When a language model develops capabilities not traceable to its individual components, when a multi-agent AI system outperforms each agent on its own, or when a human-AI pair succeeds where either…Birthday Estimators Are Uniformly Optimal for Renyi Entropy
Collisions are a basic probe of unknown distributions, used for testing and for counting substructures in graphs, and they underlie Rényi entropy, a fundamental measure of uncertainty with…Entanglement Distribution in Quantum Switch Networks: Memory Limits and Achievability
We study the minimum persistent memory required to distribute a graph state through a quantum switch.From Common Information to Canonical Correlation Analysis and Beyond: Bridging Information Theory, Signal Processing, and Machine Learning
Many problems in signal processing, machine learning, and neuroimaging provide several jointly observed measurements of one process, each mixing a component common to all of them with a component…