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Modern Logics, as formulated notably by Frege, Russell and Tarski involved basic assumptions about Natural Languages in general and Indo-European Languages in particular, which are contested by Linguists. Based upon those assumptions,…

Computation and Language · Computer Science 2023-10-31 Elnaserledinellah Mahmood Abdelwahab

Recently, a novel form of audio partial forgery has posed challenges to its forensics, requiring advanced countermeasures to detect subtle forgery manipulations within long-duration audio. However, existing countermeasures still serve a…

Multimedia · Computer Science 2024-07-24 Junyan Wu , Wei Lu , Xiangyang Luo , Rui Yang , Qian Wang , Xiaochun Cao

In this paper, we develop a general theory of truncated inverse binomial sampling. In this theory, the fixed-size sampling and inverse binomial sampling are accommodated as special cases. In particular, the classical Chernoff-Hoeffding…

Statistics Theory · Mathematics 2019-08-20 Xinjia Chen

We study the problem of obtaining lower bounds for polynomial calculus (PC) and polynomial calculus resolution (PCR) on proof degree, and hence by [Impagliazzo et al. '99] also on proof size. [Alekhnovich and Razborov '03] established that…

Computational Complexity · Computer Science 2015-05-07 Mladen Mikša , Jakob Nordström

The random 3-satisfiability (3-SAT) problem is in the unsatisfiable (UNSAT) phase when the clause density $\alpha$ exceeds a critical value $\alpha_s \approx 4.267$. However, rigorously proving the unsatisfiability of a given large 3-SAT…

Computational Complexity · Computer Science 2013-07-29 Lu-Lu Wu , Hai-Jun Zhou , Mikko Alava , Erik Aurell , Pekka Orponen

In this note, we propose a framework for proving computational lower bounds in norm approximation by leveraging a reverse detection--estimation gap. The starting point is a testing problem together with an estimator whose error is…

Statistics Theory · Mathematics 2026-04-07 Runshi Tang , Yuefeng Han , Anru R. Zhang

We significantly strengthen and generalize the theorem lifting Nullstellensatz degree to monotone span program size by Pitassi and Robere (2018) so that it works for any gadget with high enough rank, in particular, for useful gadgets such…

Computational Complexity · Computer Science 2020-01-08 Susanna F. de Rezende , Or Meir , Jakob Nordström , Toniann Pitassi , Robert Robere , Marc Vinyals

Counterfactual explanations can be obtained by identifying the smallest change made to a feature vector to qualitatively influence a prediction; for example, from 'loan rejected' to 'awarded' or from 'high risk of cardiovascular disease' to…

Machine Learning · Computer Science 2020-05-05 Martin Pawelczyk , Johannes Haug , Klaus Broelemann , Gjergji Kasneci

The fundamental lower size limit in wavelength selecting structures is explored with the aid of the Heisenberg uncertainty principle. The analysis shows that for a given wavelength selectivity resonating structures with optical feedback…

Quantum Physics · Physics 2017-07-18 A. Driessen , H. J. W. M. Hoekstra , D. J. W. Klunder , F. S. Tan

Under what condition is a random constraint satisfaction problem hard to refute by the sum-of-squares (SoS) algorithm? A sufficient condition is t-wise uniformity, that is, each constraint has a t-wise uniform distribution of satisfying…

Computational Complexity · Computer Science 2026-05-01 Siu On Chan , Tommaso d'Orsi , Jeff Xu

Conformal prediction is a powerful tool to generate uncertainty sets with guaranteed coverage using any predictive model, under the assumption that the training and test data are i.i.d.. Recently, it has been shown that adversarial examples…

Machine Learning · Computer Science 2024-05-01 Ge Yan , Yaniv Romano , Tsui-Wei Weng

Given a CNF formula F on n variables, the problem of model counting or #SAT is to compute the number of satisfying assignments of F . Model counting is a fundamental but hard problem in computer science with varied applications. Recent…

Data Structures and Algorithms · Computer Science 2020-05-01 Kuldeep S. Meel , S. Akshay

A large deviation analysis of the solving complexity of random 3-Satisfiability instances slightly below threshold is presented. While finding a solution for such instances demands an exponential effort with high probability, we show that…

Disordered Systems and Neural Networks · Physics 2009-11-07 S. Cocco , R. Monasson

We study approximation in the unit interval by rational numbers whose numerators are selected randomly with certain probabilities. Previous work showed that an analogue of Khintchine's Theorem holds in a similar random model and raised the…

Number Theory · Mathematics 2019-09-17 Laima Kaziulytė , Felipe A. Ramírez

Probabilistic decoding in Large Language Models (LLMs) often yields inconsistent outputs, particularly on complex or long-form questions. Self-Consistency (SC) mitigates this for short-form QA by majority voting over exact strings, whereas…

Computation and Language · Computer Science 2026-03-02 Jungsuk Oh , Jay-Yoon Lee

Large language models (LLMs) need reliable test-time control of hallucinations. Existing conformal methods for LLMs typically provide only \emph{marginal} guarantees and rely on a single global threshold, which can under-cover hard prompts,…

Machine Learning · Computer Science 2026-03-31 Kai Ye , Qingtao Pan , Shuo Li

Using a recently introduced algorithm for simulating percolation in microcanonical (fixed-occupancy) samples, we study the convergence with increasing system size of a number of estimates for the percolation threshold for an open system…

Statistical Mechanics · Physics 2009-11-07 R. M. Ziff , M. E. J. Newman

The extent to which neural networks are able to acquire and represent symbolic rules remains a key topic of research and debate. Much current work focuses on the impressive capabilities of large language models, as well as their often…

Machine Learning · Computer Science 2025-06-11 Anna Langedijk , Jaap Jumelet , Willem Zuidema

Random Fourier Features (RFF) demonstrate wellappreciated performance in kernel approximation for largescale situations but restrict kernels to be stationary and positive definite. And for non-stationary kernels, the corresponding RFF could…

Machine Learning · Statistics 2021-04-15 Qin Luo , Kun Fang , Jie Yang , Xiaolin Huang

Feasible interpolation is a general technique for proving proof complexity lower bounds. The monotone version of the technique converts, in its basic variant, lower bounds for monotone Boolean circuits separating two NP-sets to proof…

Computational Complexity · Computer Science 2022-01-19 Lukáš Folwarczný