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LangPro is an automated theorem prover for natural language (https://github.com/kovvalsky/LangPro). Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic…

Computation and Language · Computer Science 2017-09-01 Lasha Abzianidze

We further develop the theoretical framework of proof mining, a program in mathematical logic that seeks to quantify and extract computational information from prima facie `non-computational' proofs from the mainstream mathematical…

Logic · Mathematics 2025-07-15 Nicholas Pischke

Reliable autoformalization remains challenging even in the era of large language models (LLMs). The scarcity of high-quality training data is a major bottleneck. Expert annotation requires substantial time and deep expertise in both…

Artificial Intelligence · Computer Science 2026-03-12 Param Biyani , Shashank Kirtania , Yasharth Bajpai , Sumit Gulwani , Ashish Tiwari

This paper presents a new system of logic, LF, that is intended to be used as the foundation of the formalization of science. That is, deductive validity according to LF is to be used as the criterion for assessing what follows from the…

Logic · Mathematics 2024-01-23 Zachary Goodsell , Juhani Yli-Vakkuri

Large formal mathematical libraries consist of millions of atomic inference steps that give rise to a corresponding number of proved statements (lemmas). Analogously to the informal mathematical practice, only a tiny fraction of such…

Artificial Intelligence · Computer Science 2014-02-17 Cezary Kaliszyk , Josef Urban

This paper presents an approach to lemma synthesis to support advanced inductive entailment procedures based on separation logic. We first propose a mechanism where lemmas are automatically proven and systematically applied. The lemmas may…

Programming Languages · Computer Science 2018-05-15 Quang Loc Le

Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to…

Software Engineering · Computer Science 2019-11-21 Jingyi Wang , Jun Sun , Shengchao Qin , Cyrille Jegourel

Large Language Models (LLMs) demonstrate impressive mathematical reasoning abilities, but their solutions frequently contain errors that cannot be automatically checked. Formal theorem proving systems such as Lean 4 offer automated…

Artificial Intelligence · Computer Science 2026-03-18 Sumanth Varambally , Thomas Voice , Yanchao Sun , Zhifeng Chen , Rose Yu , Ke Ye

Isabelle is a generic theorem prover with a fragment of higher-order logic as a metalogic for defining object logics. Isabelle also provides proof terms. We formalize this metalogic and the language of proof terms in Isabelle/HOL, define an…

Logic in Computer Science · Computer Science 2021-11-25 Tobias Nipkow , Simon Roßkopf

This paper argues that mathematical objects are constructions and that constructions introduce a flexibility in the ways that mathematical objects are represented (as sets of binary sequences for example) and presented (in a particular…

Logic · Mathematics 2020-01-14 Andrew Powell

We introduce our implementation in HOL Light of the metatheory for G\"odel-L\"ob provability logic (GL), covering soundness and completeness w.r.t. possible world semantics and featuring a prototype of a theorem prover for GL itself. The…

Logic in Computer Science · Computer Science 2023-10-13 Marco Maggesi , Cosimo Perini Brogi

We are interested in understanding how well Transformer language models (TLMs) can perform reasoning tasks when trained on knowledge encoded in the form of natural language. We investigate their systematic generalization abilities on a…

Machine Learning · Computer Science 2020-10-22 Nicolas Gontier , Koustuv Sinha , Siva Reddy , Christopher Pal

Large language models (LLMs) are beginning to reshape how chemists plan and run reactions in organic synthesis. Trained on millions of reported transformations, these text-based models can propose synthetic routes, forecast reaction…

Artificial Intelligence · Computer Science 2025-08-08 Kartar Kumar Lohana Tharwani , Rajesh Kumar , Sumita , Numan Ahmed , Yong Tang

A set of linear second-order differential equations is converted into a semigroup, whose algebraic structure is used to generate many novel equations. Two independent methods that can be used to derive the equations of the semigroup are…

Mathematical Physics · Physics 2020-07-22 Zdzislaw Musielak , Niyousha Davachi , Marialis Rosario-Franco

With the growing popularity of Large Reasoning Models and their results in solving mathematical problems, it becomes crucial to measure their capabilities. We introduce a pipeline for both automatic and interactive verification as a more…

Artificial Intelligence · Computer Science 2026-02-25 Varvara Sazonova , Dmitri Shmelkin , Stanislav Kikot , Vasily Motolygin

Unlike mathematics, in which the notion of truth might be abstract, in physics, the emphasis must be placed on algorithmic procedures for obtaining numerical results subject to the experimental verifiability. For, a physical science is…

Quantum Physics · Physics 2015-12-02 Arkady Bolotin

General-purpose Large Language Models (LLMs) have achieved remarkable success in intelligence, performing comparably to human experts on complex reasoning tasks such as coding and mathematical reasoning. However, generating formal proofs in…

The paper proves that quantum mechanics is compatible with the constructive realism of modern philosophy of science. The proof is based on the observation that properties of quantum systems that are uniquely determined by their preparations…

Quantum Physics · Physics 2013-06-17 Petr Hajicek

The demand for synthetic data in mathematical reasoning has increased due to its potential to enhance the mathematical capabilities of large language models (LLMs). However, ensuring the validity of intermediate reasoning steps remains a…

Artificial Intelligence · Computer Science 2026-01-19 Joshua Ong Jun Leang , Giwon Hong , Wenda Li , Shay B. Cohen

We study the GENERIC hydrodynamic theory for relativistic liquids formulated by Ottinger and collaborators. We use the maximum entropy principle to derive its conditions for linear stability (in an arbitrary reference frame) and for…

General Relativity and Quantum Cosmology · Physics 2023-03-16 Lorenzo Gavassino , Marco Antonelli
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