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Language models have become increasingly powerful tools for formal mathematical reasoning. However, most existing approaches rely exclusively on either large general-purpose models or smaller specialized models, each with distinct…

Artificial Intelligence · Computer Science 2025-07-22 Nicolas Wischermann , Claudio Mayrink Verdun , Gabriel Poesia , Francesco Noseda

Advances in Large Language Models (LLMs) have spurred a wave of LLM library learning systems for mathematical reasoning. These systems aim to learn a reusable library of tools, such as formal Isabelle lemmas or Python programs that are…

Machine Learning · Computer Science 2024-10-29 Ian Berlot-Attwell , Frank Rudzicz , Xujie Si

The heterogeneous nature of the logical foundations used in different interactive proof assistant libraries has rendered discovery of similar mathematical concepts among them difficult. In this paper, we compare a previously proposed…

Logic in Computer Science · Computer Science 2021-07-22 Qingxiang Wang , Cezary Kaliszyk

We present a reinforcement learning (RL) based guidance system for automated theorem proving geared towards Finding Longer Proofs (FLoP). Unlike most learning based approaches, we focus on generalising from very little training data and…

Logic in Computer Science · Computer Science 2021-06-30 Zsolt Zombori , Adrián Csiszárik , Henryk Michalewski , Cezary Kaliszyk , Josef Urban

In systems verification we are often concerned with multiple, inter-dependent properties that a program must satisfy. To prove that a program satisfies a given property, the correctness of intermediate states of the program must be…

Logic in Computer Science · Computer Science 2024-10-23 Danielle Matichuk

Programs using random values can either make all choices in advance (eagerly) or sample as needed (lazily). In formal proofs, we focus on indistinguishability between two lazy programs, a common requirement in the random oracle model (ROM).…

Cryptography and Security · Computer Science 2023-11-30 Roberto Metere , Changyu Dong

Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been shown to perform better than inductive learners. However,…

Machine Learning · Computer Science 2011-01-26 Ridwan Al Iqbal

Interactive Theorem Provers (ITPs) are an indispensable tool in the arsenal of formal method experts as a platform for construction and (formal) verification of proofs. The complexity of the proofs in conjunction with the level of expertise…

Logic in Computer Science · Computer Science 2023-04-21 Eric Yeh , Briland Hitaj , Sam Owre , Maena Quemener , Natarajan Shankar

We extend a semantic verification framework for hybrid systems with the Isabelle/HOL proof assistant by an algebraic model for hybrid program stores, a shallow expression model for hybrid programs and their correctness specifications, and…

Logic in Computer Science · Computer Science 2021-06-14 Simon Foster , Jonathan Julián Huerta y Munive , Mario Gleirscher , Georg Struth

We envision a continuous collaborative learning system where groups of LLM agents work together to solve reasoning problems, drawing on memory they collectively build to improve performance as they gain experience. This work establishes the…

Artificial Intelligence · Computer Science 2025-03-11 Julie Michelman , Nasrin Baratalipour , Matthew Abueg

Formal, automated theorem proving has long been viewed as a challenge to artificial intelligence. We introduce here a new approach to computer theorem proving, one that employs specialized language models for Lean4 proof generation combined…

Artificial Intelligence · Computer Science 2025-12-17 Kelly J. Davis

This paper presents Holbert: a work-in-progress pedagogical proof assistant and online textbook platform, aimed at the educational use-case, specifically for the teaching of programming language theory. Holbert allows proof exercises and…

Logic in Computer Science · Computer Science 2022-10-21 Liam O'Connor , Rayhana Amjad

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

Recent advancements in the coding, reasoning, and tool-using abilities of LLMs have spurred interest in library learning (i.e., online learning through the creation, storage, and retrieval of reusable and composable functions, knowledge,…

Machine Learning · Computer Science 2025-04-07 Ian Berlot-Attwell , Frank Rudzicz , Xujie Si

Dependent type theory gives an expressive type system facilitating succinct formalizations of mathematical concepts. In practice, it is mainly used for interactive theorem proving with intensional type theories, with PVS being a notable…

Logic in Computer Science · Computer Science 2024-10-21 Johannes Niederhauser , Chad E. Brown , Cezary Kaliszyk

In logical reasoning, it is often the case that only some of a collection of assumptions are needed to reach a conclusion. A strengthening lemma is an assertion that a given conclusion is independent in this sense of a particular…

Logic in Computer Science · Computer Science 2017-05-26 Dawn Michaelson

We observe today a large diversity of proof systems. This diversity has the negative consequence that a lot of theorems are proved many times. Unlike programming languages, it is difficult for these systems to co-operate because they do not…

Logic in Computer Science · Computer Science 2018-07-06 François Thiré

This paper presents experiments on common knowledge logic, conducted with the help of the proof assistant Coq. The main feature of common knowledge logic is the eponymous modality that says that a group of agents shares a knowledge about a…

Artificial Intelligence · Computer Science 2008-01-16 Pierre Lescanne

We introduce the framework of "social learning" in the context of large language models (LLMs), whereby models share knowledge with each other in a privacy-aware manner using natural language. We present and evaluate two approaches for…

Machine Learning · Computer Science 2024-02-09 Amirkeivan Mohtashami , Florian Hartmann , Sian Gooding , Lukas Zilka , Matt Sharifi , Blaise Aguera y Arcas

Deep and shallow embeddings of non-classical logics in classical higher-order logic have been explored, implemented, and used in various reasoning tools in recent years. This paper presents a method for the simultaneous deployment of deep…

Logic in Computer Science · Computer Science 2025-06-03 Christoph Benzmüller