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 13
One generation of the Standard Model as a quantum error-correcting code
Together with a right-handed neutrino, the fermions of one generation of the Standard Model are labelled by five bits, a combinatorial structure tied to anomaly cancellation.Uncertainty-Aware Federated Learning for Joint Communication and Computation in XR Systems
The convergence of communication and computation, empowered by artificial intelligence (AI) enhanced capabilities, emerges as a key enabler for realizing the promising functionalities of the…GPU-Accelerated Robust MA--RIS Pre-Optimization for Communication and Target Illumination
Movable antennas (MAs) and reconfigurable intelligent surfaces (RISs) offer strong spatial control for integrated sensing and communication (ISAC), but repeatedly adapting MA positions and RIS…A thermally and perturbatively stable classical spin model in two dimensions
We show that the 2D classical spin model constructed in arXiv:2605.10943 hosts many metastable states at non-zero temperature which are stable to arbitrary Hamiltonian perturbations, providing the…Area Theorems for Quantum Error Correction
The extrinsic information transfer (EXIT) and generalized EXIT (GEXIT) area theorems provide fundamental conservation laws that connect the rate of classical codes to the performance of…Digital Self-Interference Cancellation for In-Band Full-Duplex Systems Based on Transformer Neural Operators
Digital-domain self-interference cancellation is essential in in-band full-duplex radios after passive suppression and analog cancellation.High-Probability Regret Bounds for Feel-Good Thompson Sampling
Feel-good Thompson sampling (FGTS) augments the posterior of vanilla Thompson sampling with an exploration term that favors reward functions with high predicted optimal values.Undirected Network Coding and Faster External-Memory Integer Sorting
Network coding allows intermediate nodes to combine messages.Exact Cap Response and Aperture Selection for Molecular Communication under Aligned Drift
Spatial reception under directed molecule transport requires balancing useful molecule capture against intersymbol interference (ISI).Analog RF Computing for Integrated Data and AI Flows Over Wireless Networks
Many resource-constrained edge devices require artificial intelligence (AI) services but are not powerful enough to store or execute neural networks (NNs).Defining and Generating Compositional Structure
Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while further compositional hierarchies appear within…textGrain watermarking is harder to detect: can sum-tests still do it optimally?
Watermarking embeds an imperceptible signal in text from large language models that is statistically detectable with a secret key.Rarity Determines Minimax Rates of Semantic Entropy From Weak Pairwise Judgments With a Known Channel
The semantic entropy of a language model is the entropy of the meanings of its sampled answers.Optimal Support Size Testing
We present an optimal tester for support size that determines whether an unknown probability distribution is supported on $n$ elements or $\varepsilon$-far away (in total variation distance) with…Relative-Entropy Geometry and Convergence in Nonconvex Wiretap Optimization
We develop and analyze an entropic descent method for a nonconvex optimization problem on probability simplices arising in classical and quantum secure communication.Gaussian entanglement and quantum communication: geodesic optimization and multimode bounds
Loss and noise limit the use of light to distribute entanglement, transmit quantum information, and establish secret keys.Delay Complexity Dimension: Learning with Delayed and Censored Labels
We study PAC learning of binary classifiers when labels arrive after random delays and are censored beyond an observation window $W$.When Does Compensating Inherited Quantization Error Help? Mean-Square Guarantees for Layer-Wise Quantization and Their Limits
Layer-wise post-training quantization methods let each layer compensate for the quantization error inherited from earlier layers.Classical and Quantum Information Measures Characterizing Convertibility: An Axiomatic Approach
In this PhD thesis, we take an axiomatic approach to studying multivariate divergences, which are measures of the information content of a tuple of classical or quantum states.Pathfinder-BP: A Low-Latency Recursive Decoder for Topological Codes
We propose Pathfinder-BP, a recursive decoder for topological quantum codes that combines belief propagation with controlled bit-flipping.