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 19
Learning Local Fermionic Lindbladians under Parity Superselection
Parity superselection forbids direct measurement of odd Majorana observables.AIR-LLM: Broadcasting AI Weights over Radio for Memory-Free Edge LLM Inference via RF Computing
Next-generation large language models (LLMs) are expanding from the cloud to ubiquitous edge devices.Good Quantum Locally Testable Codes from Lossless Cubical Complexes
Sipser and Spielman constructed LDPC codes from either bipartite \emph{spectral} expanders or one-sided \emph{lossless} expanders.Interpreting Reasoning of Large Language Models via Partial Information Decomposition
Large reasoning models (LRMs) have achieved substantial improvements in solving complex mathematical problems, but often produce lengthy, repetitive, or erroneous reasoning trajectories.Progressive-Resolution Secure Aggregation for Federated Learning
Secure aggregation lets a server recover an aggregate of client updates without observing any individual update, but conventional protocols fix the aggregate precision when clients upload.Parameter-Free Interval-Dynamic Regret under Heavy-Tailed Noise
We study online convex optimization with one unbiased stochastic subgradient per round and an unknown finite conditional $p$th noise moment, $1<p\le2$.Evolving Towards Better Codes: LLM-Guided Search for High-Distance Binary Linear Codes
Evolutionary program search driven by large language models (LLMs) has produced record-breaking constructions for open problems in combinatorics and beyond.A Memory-Magic Exchange Law in Streaming Clifford+T Compilation
A phase that reaches a fault-tolerant processor in additive pieces can be remembered until the last piece arrives, or executed on arrival: the first option costs classical memory carried across…End-to-End Optical Semantic Communication over a Nonlinear WDM Fiber Link
Emerging optical-network applications increasingly use received data for inference and control rather than exact source reproduction, creating an opportunity to trade bit-level fidelity for greater…RAVEN: Receiver-Conditioned Action-Value Encoding for Finite-Alphabet Multi-Agent Communication
A message drawn from a small alphabet helps a teammate only if it keeps the distinctions that change that teammate's next decision.On Task Scope and Information Retention in Source Coding
We argue that dividing codec design into Coding for Machines (CfM) and Coding for Humans (CfH) is a misleading distinction for deciding what information a codec may discard.Resonance Breaking in Noisy Shor's Algorithm
We argue that the exponential quantum advantage in Shor's algorithm is broken under one-layer depolarizing noise of arbitrary small error rate, by analyzing a resonance breaking phenomenon in noisy…Mutual Information Constrained Chernoff Bottleneck
The classical information bottleneck (IB) measures the relevance of a representation $U$ of $X$ to a target $Y$ by $I(U;Y)$, which does not directly characterize the error of downstream decisions.The exact strong converse exponent for private communication over quantum channels
We determine the exact strong converse exponent for secret-key transmission and generation over general finite-dimensional quantum wiretap channels, measuring reliability and secrecy jointly by…Derandomizing Dense Binary Hypervector Codebooks for Quantized Scalars
Hyperdimensional computing and vector symbolic architectures often represent quantized scalar levels by dense binary codebooks whose level-to-level similarity is intended to follow a prescribed…Monotonicity of the Rényi channel capacity under non-signaling assisted channel simulation
We ask whether non-signaling correlations shared between the sender and receiver can increase the Rényi capacity of a classical channel.SemRD-V2X: Closure-Guided Communication with Bounded Inference for Cooperative Perception
Vehicle-to-Everything (V2X) cooperative perception improves 3-D detection by sharing intermediate features, but dense remote features may repeat context that the ego agent can infer locally.Understanding Generalization Requires Universal Induction
Classical statistical theory is insufficient to explain the successes of general-purpose AI models, because it depends on handcrafted inductive biases that it cannot justify.Information-Theoretic Analysis of Next-Token Prediction under Markovian Data
We develop an information-theoretic framework for generalization in next-token prediction under temporally dependent data.Memory in the Sky: Low-Altitude Question Answering with Multi-Agent Memory Aggregation
This paper studies low-altitude question answering (LAQA), in which distributed unmanned aerial vehicle (UAV) memories are aggregated at a ground server to answer questions about observations over a…