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The idea of this approach towards proving the consistency of Quine's New Foundations set theory is to go in a completely untyped manner. So no contemplation about types is utilized here. All conceptualization pivots around proving a handful…

Logic · Mathematics 2021-07-27 Zuhair Al-Johar

Whereas the semantics of probabilistic languages has been extensively studied, specification languages for their properties have received less attention -- with the notable exception of recent and on-going efforts by Joost-Pieter Katoen and…

Logic in Computer Science · Computer Science 2024-12-03 Einar Broch Johnsen , Eduard Kamburjan , Raúl Pardo , Erik Voogd , Andrzej Wąsowski

Argumentation is the process of constructing arguments about propositions, and the assignment of statements of confidence to those propositions based on the nature and relative strength of their supporting arguments. The process is modelled…

Artificial Intelligence · Computer Science 2013-03-08 John Fox , Paul J. Krause , Morten Elvang-Gøransson

The Cornell Semantic Parsing Framework (SPF) is a learning and inference framework for mapping natural language to formal representation of its meaning.

Computation and Language · Computer Science 2016-10-11 Yoav Artzi

The proof of the relative consistency of the axiom of choice has been mechanized using Isabelle/ZF. The proof builds upon a previous mechanization of the reflection theorem. The heavy reliance on metatheory in the original proof makes the…

Logic in Computer Science · Computer Science 2021-04-27 Lawrence C. Paulson

In the theory of programming languages, type inference is the process of inferring the type of an expression automatically, often making use of information from the context in which the expression appears. Such mechanisms turn out to be…

Logic in Computer Science · Computer Science 2012-05-10 Jeremy Avigad

Polynomial inequalities lie at the heart of many mathematical disciplines. In this paper, we consider the fundamental computational task of automatically searching for proofs of polynomial inequalities. We adopt the framework of…

Machine Learning · Computer Science 2019-06-06 Alhussein Fawzi , Mateusz Malinowski , Hamza Fawzi , Omar Fawzi

Formal methods apply algorithms based on mathematical principles to enhance the reliability of systems. It would only be natural to try to progress from verification, model checking or testing a system against its formal specification into…

Software Engineering · Computer Science 2014-02-28 Gal Katz , Doron Peled

Cut-elimination theorems constitute one of the most important classes of theorems of proof theory. Since Gentzen's proof of the cut-elimination theorem for the system $\mathbf{LK}$, several other proofs have been proposed. Even though the…

Logic · Mathematics 2024-10-08 Sayantan Roy

In the context of natural deduction for propositional classical logic, with classicality given by the inference rule reductio ad absurdum, we investigate the De Morgan translation of disjunction in terms of negation and conjunction. Once…

Logic in Computer Science · Computer Science 2016-06-22 José Espírito Santo

To assist non-specialists in formulating database queries, multiple frameworks that automatically infer queries from a set of examples have been proposed. While highly useful, a shortcoming of the approach is that if users can only provide…

Databases · Computer Science 2016-05-17 Daniel Deutch , Amir Gilad

We present an exact Bayesian inference method for discrete statistical models, which can find exact solutions to a large class of discrete inference problems, even with infinite support and continuous priors. To express such models, we…

Programming Languages · Computer Science 2023-11-08 Fabian Zaiser , Andrzej S. Murawski , Luke Ong

Universal probabilistic programming systems (PPSs) provide a powerful framework for specifying rich probabilistic models. They further attempt to automate the process of drawing inferences from these models, but doing this successfully is…

Machine Learning · Statistics 2020-07-17 Yuan Zhou , Hongseok Yang , Yee Whye Teh , Tom Rainforth

Reasoning is a fundamental substrate for solving novel and complex problems. Deliberate efforts in learning and developing frameworks around System 2 reasoning have made great strides, yet problems of sufficient complexity remain largely…

Computation and Language · Computer Science 2024-10-18 Matthew Ho , Vincent Zhu , Xiaoyin Chen , Moksh Jain , Nikolay Malkin , Edwin Zhang

The rapid evolution of artificial intelligence has led to expectations of transformative impact on science, yet current systems remain fundamentally limited in enabling genuine scientific discovery. This perspective contends that progress…

Artificial Intelligence · Computer Science 2025-12-16 Karthik Duraisamy

The Wald development of statistical decision theory addresses decision making with sample data. Wald's concept of a statistical decision function (SDF) embraces all mappings of the form [data -> decision]. An SDF need not perform…

Econometrics · Economics 2019-09-17 Charles F. Manski

Although most of the automated theorem-proving approaches depend on formal proof systems, informal theorem proving can align better with large language models' (LLMs) strength in natural language processing. In this work, we identify a…

Artificial Intelligence · Computer Science 2026-04-20 Yunhe Li , Hao Shi , Bowen Deng , Wei Wang , Mengzhe Ruan , Hanxu Hou , Zhongxiang Dai , Siyang Gao , Chao Wang , Shuang Qiu , Linqi Song

Deductive reasoning plays a pivotal role in the formulation of sound and cohesive arguments. It allows individuals to draw conclusions that logically follow, given the truth value of the information provided. Recent progress in the domain…

Computation and Language · Computer Science 2024-06-04 Philipp Mondorf , Barbara Plank

Inductive reasoning enables humans to infer abstract rules from limited examples and apply them to novel situations. In this work, we compare an LLM-based hypothesis search framework with direct program generation approaches on few-shot…

Artificial Intelligence · Computer Science 2025-09-03 Aishni Parab , Hongjing Lu , Ying Nian Wu , Sumit Gulwani

Drawing appropriate defeasible inferences has been proven to be one of the most pervasive puzzles of natural language processing and a recurrent problem in pragmatics. This paper provides a theoretical framework, called ``stratified…

cmp-lg · Computer Science 2008-02-03 Daniel Marcu , Graeme Hirst
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