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.
Get the few papers worth your time in Information Theory every morning.
Follow Information Theory and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 10
ATEMPO: Amortized Transfer Entropy Model Per-lag Over-Time
When one time series informs another, the delay at which that information arrives determines if models can utilize this relationship effectively.PDE-Based Bounds on Optimal Exponents in Active Simple Hypothesis Testing
We present general upper and lower bounds on the optimal error exponent for the Active Simple Hypothesis Testing (ASHT) problem.Ancestor Lifting of Quasi-Cyclic Additive Codes and Certified Quantum Codes
Additive codes over $\Ffour$ that are self-orthogonal under the trace inner product correspond to binary quantum stabilizer codes.Variable-Length Feedback Coding With Universal Decoding and Bandit Channel Selection
We study variable-length feedback (VLF) coding over $K$ additive white Gaussian noise (AWGN) channels whose noise variances are unknown to both terminals but lie in a known interval.Universal Short-Time Fourier Transform: Data-Adaptive Window-Length Selection for Time-Frequency Analysis
The short-time Fourier transform (STFT) characterizes the local frequency content of time-varying signals by evaluating the discrete Fourier transform over a sliding analysis window.Twisted Fourier Analysis of Quantum Weight Enumerators
A unified Fourier framework for quantum weight enumerators of prime-power-dimensional qudits is developed in this paper.Federated Learning for Semantic Communications over Multiple Access Channels
This paper presents a federated learning (FL) framework for semantic communication (SemCom) over the multiple access channel (MAC), where multiple distributed transmitters simultaneously convey…Integral Probability Boundaries
Bounds based on Integral Probability Metrics (IPMs) are ubiquitous in machine learning and statistics, appearing, e.g., in generalization, alignment, fairness, and privacy.Linear Hashing Is Poissonesque
The Poisson approximation theorem states that when $m$ balls are tossed uniformly and randomly into $n$ bins, the distribution of the bin loads can sometimes be approximated by $n$ independent…Information-Theoretic Secure Aggregation With Heterogeneous Client Quantization
In federated learning (FL), secure aggregation enables a server to compute the sum of local model updates of $N$ clients, without revealing any information on the individual model updates to the…What Should an Information Bottleneck Encoder Learn? Separating Representation Learning from Rate Control
The information bottleneck (IB) trades compression of an input $X$ against prediction of a target $Y$ through a multiplier $β=1/λ$, yet each operating point is usually served by training, or fully…Persistence, Exposure, and Credit Routing in Linear Temporal Predictive Coding
Temporal Predictive Coding (tPC) networks offer a layer-local alternative to backpropagation.Multi-view Semantic-aware Resource Allocation for Edge AI
Semantic communication is emerging as a pivotal paradigm to overcome wireless resource scarcity in 6G networks.Structured Time-Frequency Representation for Channel Prediction
Accurate CSI forecasting is essential for mitigating channel aging and supporting reliable downlink transmission in high-mobility wireless systems.Distributed LLM Inference via Communication-Efficient Speculative Decoding
Distributed speculative decoding has emerged as a promising approach for device--server collaborative large language model (LLM) inference, but its decoding speedup is often limited by the…Online Covariance Estimation for Averaged Stochastic Gradient Descent on Riemannian Manifolds
We study online inference for averaged Riemannian stochastic gradient descent (RSGD) when the unknown parameter lies on a manifold.Joint End-to-End Training of Weighted BP Decoder Ensembles
Ensemble decoding improves decoding reliability by combining component decoders with complementary failure events.Learning Representative Port Subsets for Efficient Fluid Antenna Systems
Fluid antenna systems (FASs) provide many candidate ports, but probing all ports for each channel realization incurs substantial online overhead.StarRTT: An End-to-End Real-Time Framework for Blind Zone-Free RTT Prediction in Starlink LEO Satellite Networks
Low Earth Orbit (LEO) satellite mega-constellations such as Starlink require frequent handovers due to high orbital velocities, resulting in substantial Round-Trip Time (RTT) fluctuations.Logarithmic Separation between LZ77 and LZ-End and Grammar Compression
We show that there is a logarithmic separation between LZ77 and LZ-End, and between LZ77 and grammar compression.