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The expression problem describes a fundamental tradeoff between two types of extensibility: extending a type with new operations, such as by pattern matching on an algebraic data type in functional programming, and extending a type with new…

Programming Languages · Computer Science 2025-11-21 Bohdan Liesnikov , David Binder , Tim Süberkrüb

We prove the uniform Lyndon interpolation property (ULIP) of some extensions of the pure logic of necessitation $\mathbf{N}$. For any $m, n \in \mathbb{N}$, $\mathbf{N}^+\mathbf{A}_{m,n}$ is the logic obtained from $\mathbf{N}$ by adding a…

Logic · Mathematics 2025-08-19 Yuta Sato

Continual learning (CL), which aims to learn a sequence of tasks, has attracted significant recent attention. However, most work has focused on the experimental performance of CL, and theoretical studies of CL are still limited. In…

Machine Learning · Computer Science 2023-02-14 Sen Lin , Peizhong Ju , Yingbin Liang , Ness Shroff

The simplest way to obtain continuous interpolation between two points in high dimensional space is to draw a line between them. While previous works focused on the general connectivity between model parameters, we explored linear…

Computation and Language · Computer Science 2022-11-23 Mark Rofin , Nikita Balagansky , Daniil Gavrilov

We study in this paper the function approximation error of multivariate linear extrapolation. The sharp error bound of linear interpolation already exists in the literature. However, linear extrapolation is used far more often in…

Optimization and Control · Mathematics 2026-05-20 Liyuan Cao , Zaiwen Wen , Ya-xiang Yuan

The languages accepted by finite automata are precisely the languages denoted by regular expressions. In contrast, finite automata may exhibit behaviours that cannot be described by regular expressions up to bisimilarity. In this paper, we…

Logic in Computer Science · Computer Science 2019-02-20 Jos C. M. Baeten , Bas Luttik , Tim Muller , Paul van Tilburg

Why do large language models sometimes output factual inaccuracies and exhibit erroneous reasoning? The brittleness of these models, particularly when executing long chains of reasoning, currently seems to be an inevitable price to pay for…

Machine Learning · Computer Science 2023-10-31 Bingbin Liu , Jordan T. Ash , Surbhi Goel , Akshay Krishnamurthy , Cyril Zhang

We describe some new univariate spline quasi-interpolants on uniform partitions of bounded intervals. Then we give some applications to numerical analysis: integration, differentiation and approximation of zeros.

Numerical Analysis · Mathematics 2016-08-16 Paul Sablonnière

Let X be a countably infinite set of real numbers and let Y_x, x \in X, be an independent family of stationary random subsets of the real numbers, e.g. homogeneous Poisson point processes. We give criteria for the a.s. existence of various…

Probability · Mathematics 2011-05-17 Martin P. W. Zerner

Craig's interpolation theorem (Craig 1957) is an important theorem known for propositional logic and first-order logic. It says that if a logical formula $\beta$ logically follows from a formula $\alpha$, then there is a formula $\gamma$,…

Artificial Intelligence · Computer Science 2007-05-23 Eyal Amir

Human communication is based on a variety of inferences that we draw from sentences, often going beyond what is literally said. While there is wide agreement on the basic distinction between entailment, implicature, and presupposition, the…

Computation and Language · Computer Science 2024-05-10 Polina Tsvilodub , Paul Marty , Sonia Ramotowska , Jacopo Romoli , Michael Franke

Empirical risk minimization (ERM) incentivizes models to exploit shortcuts, i.e., spurious correlations between input attributes and labels that are prevalent in the majority of the training data but unrelated to the task at hand. This…

Machine Learning · Computer Science 2025-07-09 Michalis Korakakis , Andreas Vlachos , Adrian Weller

Linear Temporal Logic (LTL) is the standard specification language for reactive systems and is successfully applied in industrial settings. However, many shortcomings of LTL have been identified in the literature, among them the limited…

Logic in Computer Science · Computer Science 2021-04-30 Daniel Neider , Alexander Weinert , Martin Zimmermann

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of concept combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC TR, whose semantics is based on the…

Artificial Intelligence · Computer Science 2019-08-13 Antonio Lieto , Gian Luca Pozzato

In-context learning (ICL) enables multimodal large language models (MLLMs) to classify images from a few labelled examples. Yet, how these models use the provided context remains opaque. While Chain-of-Thought prompting is widely used,…

Artificial Intelligence · Computer Science 2026-05-28 Carmen Quiles-Ramírez , Leticia L. Rodríguez , Nicolás Martorell , Natalia Díaz-Rodríguez

Large language models (LLMs) have demonstrated impressive capabilities in various tasks using the in-context learning (ICL) paradigm. However, their effectiveness is often compromised by inherent bias, leading to prompt brittleness, i.e.,…

Computation and Language · Computer Science 2024-12-13 Hanzhang Zhou , Zijian Feng , Zixiao Zhu , Junlang Qian , Kezhi Mao

Linear interpolation between fine-tuned checkpoints has been shown to trace the Pareto front between competing objectives, but whether extrapolative weight averaging can extend such frontiers to new checkpoints useful at inference time,…

Machine Learning · Computer Science 2026-05-28 Kunhao Zheng , Pierre Chambon , Juliette Decugis , Jonas Gehring , Taco Cohen , Benjamin Negrevergne , Gabriel Synnaeve

Admissible rules are shown to be conservatively preserved by the meet-combination of a wide class of logics. A basis is obtained for the resulting logic from bases given for the component logics. Structural completeness and decidability of…

Logic · Mathematics 2016-12-19 Joao Rasga , Cristina Sernadas , Amilcar Sernadas

Continual learning is crucial for applying machine learning in challenging, dynamic, and often resource-constrained environments. However, catastrophic forgetting - overwriting previously learned knowledge when new information is acquired -…

Machine Learning · Computer Science 2025-05-30 Filip Szatkowski , Yaoyue Zheng , Fei Yang , Bartłomiej Twardowski , Tomasz Trzciński , Joost van de Weijer

In the author's PhD thesis (2019) universal envelopes were introduced as a tool for studying the continuously obtainable information on discontinuous functions. To any function $f \colon X \to Y$ between $\operatorname{qcb}_0$-spaces one…

Logic in Computer Science · Computer Science 2023-06-22 Eike Neumann