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In this paper, we introduce novel Twin Parametric Margin Support Vector Machine (TPMSVM) models designed to address multiclass classification tasks under feature uncertainty. To handle data perturbations, we construct bounded-by-norm…

Machine Learning · Computer Science 2026-04-29 Renato De Leone , Francesca Maggioni , Andrea Spinelli

We present a formal tool for verification of multivariate nonlinear inequalities. Our verification method is based on interval arithmetic with Taylor approximations. Our tool is implemented in the HOL Light proof assistant and it is capable…

Logic in Computer Science · Computer Science 2013-05-22 Alexey Solovyev , Thomas C. Hales

This paper presents LIBTwinSVM, a free, efficient, and open source library for Twin Support Vector Machines (TSVMs). Our library provides a set of useful functionalities such as fast TSVMs estimators, model selection, visualization, a…

Machine Learning · Computer Science 2020-01-29 Amir M. Mir , Mahdi Rahbar , Jalal A. Nasiri

Automated theorem provers (ATPs) can disprove conjectures by saturating a set of clauses, but the resulting saturated sets are opaque certificates. In the unit equational fragment, a saturated set can in fact be read as a convergent rewrite…

Logic in Computer Science · Computer Science 2026-02-19 Mikoláš Janota , Michael Rawson , Stephan Schulz

We present a tool that automates termination proofs for recursive definitions by mining existing termination theorems.

Logic in Computer Science · Computer Science 2018-10-16 Matt Kaufmann

Statistical hypothesis testing and effect size measurement are routine parts of quantitative research. Advancements in computer processing power have greatly improved the capability of statistical inference through the availability of…

Methodology · Statistics 2024-01-18 Michael J. Crosse , John J. Foxe , Sophie Molholm

We introduce a proof recommender system for the HOL4 theorem prover. Our tool is built upon a transformer-based model [2] designed specifically to provide proof assistance in HOL4. The model is trained to discern theorem proving patterns…

Logic in Computer Science · Computer Science 2025-01-13 Nour Dekhil , Adnan Rashid , Sofiene Tahar

Test-time reinforcement learning (TTRL) has emerged as a promising paradigm for self-evolving large reasoning models (LRMs), enabling online adaptation on unlabeled test inputs via self-induced rewards through majority voting. However, a…

Artificial Intelligence · Computer Science 2026-03-03 Ruotong Liao , Nikolai Röhrich , Xiaohan Wang , Yuhui Zhang , Yasaman Samadzadeh , Volker Tresp , Serena Yeung-Levy

Model checking and automated theorem proving are two pillars of formal methods. This paper investigates model checking from an automated theorem proving perspective, aiming at combining the expressiveness of automated theorem proving and…

Logic in Computer Science · Computer Science 2017-10-03 Ying Jiang , Jian Liu , Gilles Dowek , Kailiang Ji

We present a trustworthy connection between the Leon verification system and the Isabelle proof assistant. Leon is a system for verifying functional Scala programs. It uses a variety of automated theorem provers (ATPs) to check verification…

Logic in Computer Science · Computer Science 2016-07-07 Lars Hupel , Viktor Kuncak

The automated generation of exercises may substantially reduce the time educators devote to manual exercise design. A major obstacle to the integration of such automation into teaching practice, however, lies in the ability to control the…

Logic in Computer Science · Computer Science 2026-03-10 João Mendes , João Marcos , Patrick Terrematte

Theorem provers are important tools for people working in formal verification. There are a myriad of interactive systems available today, with varying features and approaches motivating their development. These design choices impact their…

Logic in Computer Science · Computer Science 2025-09-19 Harrison Oates , Hyeonggeun Yun , Nikhila Gurusinghe

Large Language Models (LLMs) have shown promising results in automating formal verification. However, existing approaches treat proof generation as a static, end-to-end prediction over source code, relying on limited verifier feedback and…

Programming Languages · Computer Science 2026-03-31 Jun Yang , Yuechun Sun , Yi Wu , Rodrigo Caridad , Yongwei Yuan , Jianan Yao , Shan Lu , Kexin Pei

Large language models (LLMs) have shown increasing competence in solving mathematical reasoning problems. However, many open-source LLMs still struggle with errors in calculation and semantic understanding during intermediate reasoning…

Computation and Language · Computer Science 2024-12-18 Vernon Y. H. Toh , Deepanway Ghosal , Soujanya Poria

Linear algebra is a major field of numerical computation and is widely applied. Most linear algebra libraries (in most programming languages) do not statically guarantee consistency of the dimensions of vectors and matrices, causing runtime…

Programming Languages · Computer Science 2015-12-08 Akinori Abe , Eijiro Sumii

Despite substantial advances in scaling test-time compute, an ongoing debate in the community is how it should be scaled up to enable continued and efficient improvements with scaling. There are largely two approaches: first, distilling…

Machine Learning · Computer Science 2025-02-19 Amrith Setlur , Nived Rajaraman , Sergey Levine , Aviral Kumar

We explore the application of transformer-based language models to automated theorem proving. This work is motivated by the possibility that a major limitation of automated theorem provers compared to humans -- the generation of original…

Machine Learning · Computer Science 2020-09-09 Stanislas Polu , Ilya Sutskever

We are interested in identifying and enforcing the isolation requirements of a concurrent program, i.e., concurrency control that ensures that the program meets its specification. The thesis of this paper is that this can be done…

Programming Languages · Computer Science 2015-07-01 Jyotirmoy Deshmukh , G. Ramalingam , Venkatesh-Prasad Ranganath , Kapil Vaswani

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

Large language models (LLMs) can potentially help with verification using proof assistants by automating proofs. However, it is unclear how effective LLMs are in this task. In this paper, we perform a case study based on two mature Rocq…

Programming Languages · Computer Science 2025-08-27 Barış Bayazıt , Yao Li , Xujie Si