Tootfinder

This https://arxiv.org/abs/2505.18492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Enumerate-Conjecture-Prove: Formally Solving Answer-Construction Problems in Math Competitions
Mathematical reasoning lies at the heart of artificial intelligence, underpinning applications in education, program verification, and research-level mathematical discovery. Mathematical competitions, in particular, present two challenging problem types: theorem-proving, requiring rigorous proofs of stated conclusions, and answer-construction, involving hypothesizing and formally verifying mathematical objects. Large Language Models (LLMs) effectively generate creative candidate answers but str…

Modal Verification Patterns for Systems
Ismail Kuru, Colin S. Gordon
https://arxiv.org/abs/2506.01719 https://arxiv.org/pdf/2506.0171…

Modal Verification Patterns for Systems
Although they differ in the functionality they offer, low-level systems exhibit certain patterns of design and utilization of computing resources. In this paper, we argue the position that modalities, in the sense of modal logic, should be a go-to approach when specifying and verifying low-level systems code. We explain how the concept of a resource context helps guide the design of new modalities for verification of systems code, and we justify our perspective by discussing prior systems that …

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation
Jiaqi Yin, Zhan Song, Nicolas Bohm Agostini, Antonino Tumeo, Cunxi Yu
https://arxiv.org/abs/2506.02290

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation
In modern computing systems, compilation employs numerous optimization techniques to enhance code performance. Source-to-source code transformations, which include control flow and datapath transformations, have been widely used in High-Level Synthesis (HLS) and compiler optimization. While researchers actively investigate methods to improve performance with source-to-source code transformations, they often overlook the significance of verifying their correctness. Current tools cannot provide…

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This https://arxiv.org/abs/2405.17492 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

StatWhy: Formal Verification Tool for Statistical Hypothesis Testing Programs
Statistical methods have been widely misused and misinterpreted in various scientific fields, raising significant concerns about the integrity of scientific research. To mitigate this problem, we propose a tool-assisted method for formally specifying and automatically verifying the correctness of statistical programs. In this method, programmers are required to annotate the source code of the statistical programs with the requirements for these methods. Through this annotation, they are reminde…

This https://arxiv.org/abs/2502.18560 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Quantum decoherence of gravitational waves
The quantum nature of gravity remains an open question in fundamental physics, lacking experimental verification. Gravitational waves (GWs) provide a potential avenue for detecting gravitons, the hypothetical quantum carriers of gravity. However, by analogy with quantum optics, distinguishing gravitons from classical GWs requires the preservation of quantum coherence, which may be lost due to interactions with the cosmic environment causing decoherence. We investigate whether GWs retain their q…

This https://arxiv.org/abs/2505.10328 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

A Comparative Study of SMT and MILP for the Nurse Rostering Problem
The effects of personnel scheduling on the quality of care and working conditions for healthcare personnel have been thoroughly documented. However, the ever-present demand and large variation of constraints make healthcare scheduling particularly challenging. This problem has been studied for decades, with limited research aimed at applying Satisfiability Modulo Theories (SMT). SMT has gained momentum within the formal verification community in the last decades, leading to the advancement of S…

Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning
Fangyu Lei, Jinxiang Meng, Yiming Huang, Tinghong Chen, Yun Zhang, Shizhu He, Jun Zhao, Kang Liu
https://arxiv.org/abs/2506.01710

Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning
Table reasoning, encompassing tasks such as table question answering, fact verification, and text-to-SQL, requires precise understanding of structured tabular data, coupled with numerical computation and code manipulation for effective inference. Supervised fine-tuning (SFT) approaches have achieved notable success but often struggle with generalization and robustness due to biases inherent in imitative learning. We introduce Reasoning-Table, the first application of reinforcement learning (RL)…

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Rolf Drechsler
https://arxiv.org/abs/2505.23311 https://

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Verification is one of the central tasks in circuit and system design. While simulation and emulation are widely used, complete correctness can only be ensured based on formal proof techniques. But these approaches often have very high run time and memory requirements. Recently, Polynomial Formal Verification (PFV) has been introduced showing that for many instances of practical relevance upper bounds on needed resources can be given. But proofs have to be provided that are human-readable. He…