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In "Compress or Route?" (Johnson, 2026), we found that code generation tolerates aggressive prompt compression (r >= 0.6) while chain-of-thought reasoning degrades gradually. That study was limited to HumanEval (164 problems), left the…

Computation and Language · Computer Science 2026-02-19 Warren Johnson

The analysis of Tables of particle properties shows that the probability distribution of the results of physical measurements is far from the conventional Gaussian $\rho(\xi)=exp(-\xi^2/2) $, but is more likely to follow the simple…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. P. Bukhvostov

We study a random code ensemble with a hierarchical structure, which is closely related to the generalized random energy model with discrete energy values. Based on this correspondence, we analyze the hierarchical random code ensemble by…

Disordered Systems and Neural Networks · Physics 2011-02-08 Tomoyuki Obuchi , Kazutaka Takahashi , Koujin Takeda

We derive a general formula of the minimum achievable rate for fixed-to-variable length coding with a regular cost function by allowing the error probability up to a constant $\varepsilon$. For a fixed-to-variable length code, we call the…

Information Theory · Computer Science 2017-10-11 Hideki Yagi , Ryo Nomura

It is well-known that modern neural networks are vulnerable to adversarial examples. To mitigate this problem, a series of robust learning algorithms have been proposed. However, although the robust training error can be near zero via some…

Machine Learning · Computer Science 2022-10-17 Binghui Li , Jikai Jin , Han Zhong , John E. Hopcroft , Liwei Wang

We study analytically and numerically decoding properties of finite rate hypergraph-product quantum LDPC codes obtained from random (3,4)-regular Gallager codes, with a simple model of independent X and Z errors. Several non-trival lower…

Quantum Physics · Physics 2018-06-14 Alexey A. Kovalev , Sanjay Prabhakar , Ilya Dumer , Leonid P. Pryadko

The persistent storage of big data requires advanced error correction schemes. The classical approach is to use error correcting codes (ECCs). This work studies an alternative approach, which uses the redundancy inherent in data itself for…

Information Theory · Computer Science 2019-10-17 Pulakesh Upadhyaya , Anxiao Jiang

The problem of distributed testing against independence with variable-length coding is considered when the \emph{average} and not the \emph{maximum} communication load is constrained as in previous works. The paper characterizes the optimum…

Information Theory · Computer Science 2020-05-19 Sadaf Salehkalaibar , Michele Wigger

A branching process in random environment $(Z_n, n \in \N)$ is a generalization of Galton Watson processes where at each generation the reproduction law is picked randomly. In this paper we give several results which belong to the class of…

Probability · Mathematics 2008-12-15 Vincent Bansaye , Julien Berestycki

The objective of this article is to investigate the asymptotic behavior of the persistence diagrams of a random cubical filtration as the window size tends to infinity. Here, a random cubical filtration is an increasing family of random…

Probability · Mathematics 2022-10-25 Yasuaki Hiraoka , Shu Kanazawa , Jun Miyanaga , Kenkichi Tsunoda

We study principal components regression (PCR) in an asymptotic high-dimensional regression setting, where the number of data points is proportional to the dimension. We derive exact limiting formulas for the estimation and prediction…

Statistics Theory · Mathematics 2025-09-18 Alden Green , Elad Romanov

Cyclic redundancy check (CRC) codes check if a codeword is correctly received. This paper presents an algorithm to design CRC codes that are optimized for the code-specific error behavior of a specified feedforward convolutional code. The…

Information Theory · Computer Science 2015-06-10 Chung-Yu Lou , Babak Daneshrad , Richard D. Wesel

In a low-order model of the general circulation of the atmosphere we examine the predictability of threshold exceedance events of certain observables. The likelihood of such binary events -- the cornerstone also for the categoric (as…

Chaotic Dynamics · Physics 2015-10-28 Tamas Bodai

We investigate random interlacements on $\mathbb{Z}^d$ with $d \geq 3$, and derive the large deviation rate for the probability that the capacity of the interlacement set in a macroscopic box is much smaller than that of the box. As an…

Probability · Mathematics 2022-05-30 Xinyi Li , Zijie Zhuang

Raptor code ensembles with linear random outer codes in a fixed-rate setting are considered. An expression for the average distance spectrum is derived and this expression is used to obtain the asymptotic exponent of the weight…

Information Theory · Computer Science 2015-11-03 Francisco Lázaro , Enrico Paolini , Gianluigi Liva , Gerhard Bauch

In this paper, explicit error bounds are derived in the approximation of rank $k$ projections of certain $n$-dimensional random vectors by standard $k$-dimensional Gaussian random vectors. The bounds are given in terms of $k$, $n$, and a…

Probability · Mathematics 2007-06-07 Elizabeth Meckes

The DNA storage channel is considered, in which a codeword is comprised of $M$ unordered DNA molecules. At reading time, $N$ molecules are sampled with replacement, and then each molecule is sequenced. A coded-index concatenated-coding…

Information Theory · Computer Science 2022-05-23 Nir Weinberger

The problem of guessing a random string is revisited. A close relation between guessing and compression is first established. Then it is shown that if the sequence of distributions of the information spectrum satisfies the large deviation…

Information Theory · Computer Science 2010-08-12 Manjesh Kumar Hanawal , Rajesh Sundaresan

Random linear network coding is a particularly decentralized approach to the multicast problem. Use of random network codes introduces a non-zero probability however that some sinks will not be able to successfully decode the required…

Information Theory · Computer Science 2007-07-13 Adria Tauste-Campo , Alex Grant

Probabilistic Circuits (PCs) are deep generative models that support exact and efficient probabilistic inference. Yet in autoregressive language modeling, PCs still lag behind Transformer-based large language models (LLMs), suggesting an…

Machine Learning · Computer Science 2026-05-14 Zhiyu Zhao , Xuejie Liu , Muhan Zhang , Anji Liu