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Intrinsic self-correction in Large Language Models (LLMs) frequently fails in open-ended reasoning tasks due to ``hallucination snowballing,'' a phenomenon in which models recursively justify early errors during free-text reflection. While…

Computation and Language · Computer Science 2026-04-08 Hongxu Zhou

The rich body of physical theories defines the foundation of our understanding of the world. Its mathematical formulation is based on classical Aristotelian (binary) logic. In the philosophy of science the ambiguities, paradoxes, and the…

History and Philosophy of Physics · Physics 2022-04-08 Johannes Falk , Edwin Eichler , Katja Windt , Marc-Thorsten Hütt

The purpose of this paper is to develop and study recursive proofs of coinductive predicates. Such recursive proofs allow one to discover proof goals in the construction of a proof of a coinductive predicate, while still allowing the use of…

Logic in Computer Science · Computer Science 2018-02-21 Henning Basold

Despite their linguistic competence, Large Language Models (LLMs) often struggle to reason reliably and flexibly. To identify these shortcomings, we introduce the Non-Linear Reasoning (NLR) dataset, a collection of 55 unique, hand-designed…

Computation and Language · Computer Science 2025-12-02 Nasim Borazjanizadeh , Steven T. Piantadosi

Transformer-based language models have achieved significant success; however, their internal mechanisms remain largely opaque due to the complexity of non-linear interactions and high-dimensional operations. While previous studies have…

Artificial Intelligence · Computer Science 2025-02-17 Lin Zhang , Lijie Hu , Di Wang

In human consciousness perceptions are distinct or atomistic events despite being perceived by an apparently undivided inner observer. This paper applies both classical (Boolean) and quantum logic to analysis of the Liar paradox which is…

Quantum Physics · Physics 2007-05-23 Erhard Bieberich

Despite the success of test-time scaling, Large Reasoning Models (LRMs) frequently encounter repetitive loops that lead to computational waste and inference failure. In this paper, we identify a distinct failure mode termed Circular…

Artificial Intelligence · Computer Science 2026-01-12 Zenghao Duan , Liang Pang , Zihao Wei , Wenbin Duan , Yuxin Tian , Shicheng Xu , Jingcheng Deng , Zhiyi Yin , Xueqi Cheng

The formal system lambda-delta is a typed lambda calculus that pursues the unification of terms, types, environments and contexts as the main goal. lambda-delta takes some features from the Automath-related lambda calculi and some from the…

Logic in Computer Science · Computer Science 2008-09-25 F. Guidi

G\"odel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop. We introduce Polaris, a G\"odel agent for compact models that performs policy repair via…

Machine Learning · Computer Science 2026-05-15 Aditya Kakade , Vivek Srivastava , Shirish Karande

We introduce Refinement Reflection, a new framework for building SMT-based deductive verifiers. The key idea is to reflect the code implementing a user-defined function into the function's (output) refinement type. As a consequence, at uses…

Programming Languages · Computer Science 2019-07-16 Niki Vazou , Anish Tondwalkar , Vikraman Choudhury , Ryan G. Scott , Ryan R. Newton , Philip Wadler , Ranjit Jhala

Variational inequalities play a key role in machine learning research, such as generative adversarial networks, reinforcement learning, adversarial training, and generative models. This paper is devoted to the constrained variational…

Machine Learning · Computer Science 2026-05-19 Mohammad S. Alkousa , Fedor S. Stonyakin , Belal A. Alashqar , Seydamet S. Ablaev

We propose a hybrid architecture that integrates decision tree-based symbolic reasoning with the generative capabilities of large language models (LLMs) within a coordinated multi-agent framework. Unlike prior approaches that loosely couple…

Artificial Intelligence · Computer Science 2025-08-08 Andrew Kiruluta

Recent work by Woodworth et al. (2020) shows that the optimization dynamics of gradient descent for overparameterized problems can be viewed as low-dimensional dual dynamics induced by a mirror map, explaining the implicit regularization…

Machine Learning · Computer Science 2024-10-21 Shuyang Wang , Diego Klabjan

We present a sequent-style proof system for provability logic GL that admits so-called circular proofs. For these proofs, the graph underlying a proof is not a finite tree but is allowed to contain cycles. As an application, we establish…

Logic · Mathematics 2015-01-05 Daniyar Shamkanov

We present an extension of the second-order logic AF2 with iso-style inductive and coinductive definitions specifically designed to extract programs from proofs a la Krivine-Parigot by means of primitive (co)recursion principles. Our logic…

Logic in Computer Science · Computer Science 2012-03-29 Favio Ezequiel Miranda-Perea , Lourdes del Carmen González-Huesca

A new computational technique based on the symbolic description utilizing kneading invariants is proposed and verified for explorations of dynamical and parametric chaos in a few exemplary systems with the Lorenz attractor. The technique…

Chaotic Dynamics · Physics 2016-12-21 Roberto Barrio , Andrey Shilnikov , Leonid Shilnikov

Autoformalization - automatically translating natural language mathematical texts into formal proof language such as Lean4 - can help accelerate AI-assisted mathematical research, be it via proof verification or proof search. I fine-tune…

Computation and Language · Computer Science 2026-03-26 Arsen Shebzukhov

We present a novel investigation into the consistency operator ($\circ$), traditionally associated with paraconsistent logics, as a means of capturing non-normal modal classicalities within the Kripke framework. By semantically…

Logic · Mathematics 2026-02-25 Alfredo Roque Freire , Manuel António Martins

Model-based robust control requires not only accurate nominal models but also systematic uncertainty representations to guarantee stability and performance. However, constructing polytopic uncertainty models typically demands multiple…

Systems and Control · Electrical Eng. & Systems 2026-05-14 Hiroshi Okajima , Shun Shirahama , Tatsunori Hayashi , Nobutomo Matsunaga

Evaluating conversational systems in multi-turn settings remains a fundamental challenge. Conventional pipelines typically rely on manually defined rubrics and fixed conversational context$-$a static approach that limits coverage and fails…

Computation and Language · Computer Science 2026-01-21 Yunzhe Li , Richie Yueqi Feng , Tianxin Wei , Chin-Chia Hsu