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How does language inform our downstream thinking? In particular, how do humans make meaning from language--and how can we leverage a theory of linguistic meaning to build machines that think in more human-like ways? In this paper, we…

Computation and Language · Computer Science 2023-06-26 Lionel Wong , Gabriel Grand , Alexander K. Lew , Noah D. Goodman , Vikash K. Mansinghka , Jacob Andreas , Joshua B. Tenenbaum

The success of the transistor as the cornerstone of digital computation motivates analogous efforts to identify an equivalent hardware primitive, the probabilistic bit or p-bit, for the emerging paradigm of probabilistic computing. Here, we…

Computational Physics · Physics 2026-02-05 Abir Hasan , Nikhil Shukla

Probabilistic spin logic (PSL) is a recently proposed computing paradigm based on unstable stochastic units called probabilistic bits (p-bits) that can be correlated to form probabilistic circuits (p-circuits). These p-circuits can be used…

Emerging Technologies · Computer Science 2018-11-05 Ahmed Zeeshan Pervaiz , Brian M. Sutton , Lakshmi Anirudh Ghantasala , Kerem Y. Camsari

I defend an analog of probabilism that characterizes rationally coherent estimates for chances. Specifically, I demonstrate the following accuracy-dominance result for stochastic theories in the C*-algebraic framework: supposing an…

History and Philosophy of Physics · Physics 2018-09-11 Jeremy Steeger

Properties such as provable security and correctness for randomized programs are naturally expressed relationally as approximate equivalences. As a result, a number of relational program logics have been developed to reason about such…

Logic in Computer Science · Computer Science 2024-12-04 Philipp G. Haselwarter , Kwing Hei Li , Alejandro Aguirre , Simon Oddershede Gregersen , Joseph Tassarotti , Lars Birkedal

Unitary quantum theory, having no Born Rule, is non-probabilistic. Hence the notorious problem of reconciling it with the unpredictability and appearance of stochasticity in quantum measurements. Generalising and improving upon the…

Quantum Physics · Physics 2016-09-28 Chiara Marletto

We make a probabilistic analysis related to some inference rules which play an important role in nonmonotonic reasoning. In a coherence-based setting, we study the extensions of a probability assessment defined on $n$ conditional events to…

Probability · Mathematics 2013-07-19 Angelo Gilio , Giuseppe Sanfilippo

A key problem in the application of first-order probabilistic methods is the enormous size of graphical models they imply. The size results from the possible worlds that can be generated by a domain of objects and relations. One of the…

Artificial Intelligence · Computer Science 2015-04-22 Daniel Nyga , Michael Beetz

P-algebras are a non-commutative, non-associative generalization of Boolean algebras that are for quantum logic what Boolean algebras are for classical logic. P-algebras have type <X, 0, ', .> where 0 is a constant, ' is unary and . is…

Quantum Physics · Physics 2024-08-16 Daniel Lehmann

Probabilistic databases (PDBs) are used to model uncertainty in data in a quantitative way. In the standard formal framework, PDBs are finite probability spaces over relational database instances. It has been argued convincingly that this…

Databases · Computer Science 2020-01-09 Martin Grohe , Peter Lindner

Large language models (LLMs) excel at zero-shot inference but continue to struggle with complex, multi-step reasoning. Recent methods that augment LLMs with intermediate reasoning steps such as Chain of Thought (CoT) and Program of Thought…

Computation and Language · Computer Science 2025-10-28 Adam Stein , Neelay Velingker , Mayur Naik , Eric Wong

The emergence of tools based on artificial intelligence has also led to the need of producing explanations which are understandable by a human being. In most approaches, the system is considered a black box, making it difficult to generate…

Artificial Intelligence · Computer Science 2024-10-23 Germán Vidal

Probabilistic partial observability is a phenomenon occuring when computer systems are deployed in environments that behave probabilistically and whose exact state cannot be fully observed. In this work, we lay the theoretical groundwork…

Logic in Computer Science · Computer Science 2025-06-17 Tobias Gürtler , Benjamin Lucien Kaminski

Energy-based probabilistic models learned by maximizing the likelihood of the data are limited by the intractability of the partition function. A widely used workaround is to maximize the pseudo-likelihood, which replaces the global…

Statistical Mechanics · Physics 2026-03-31 Francesco D'Amico , Dario Bocchi , Luca Maria Del Bono , Saverio Rossi , Matteo Negri

We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random…

Artificial Intelligence · Computer Science 2024-05-08 Thierry Denoeux

Effective bounds on the union probability are well known to be beneficial in the analysis of stochastic problems in many areas, including probability theory, information theory, statistical communications, computing and operations research.…

Probability · Mathematics 2016-02-02 Jun Yang , Fady Alajaji , Glen Takahara

The reasoning with qualitative uncertainty measures involves comparative statements about events in terms of their likeliness without necessarily assigning an exact numerical value to these events. The paper is divided into two parts. In…

Logic · Mathematics 2024-03-18 Marta Bilkova , Sabine Frittella , Daniil Kozhemiachenko , Ondrej Majer

Probabilistic quantum cloning and identifying machines can be constructed via unitary-reduction processes [Duan and Guo, Phys. Rev. Lett. 80, 4999 (1998)]. Given the cloning (identifying) probabilities, we derive an explicit representation…

Quantum Physics · Physics 2009-10-31 Chuan-Wei Zhang , Zi-Yang Wang , Chuan-Feng Li , Guang-Can Guo

This paper introduces Probabilistic Deduction (PD) as an approach to probabilistic structured argumentation. A PD framework is composed of probabilistic rules (p-rules). As rules in classical structured argumentation frameworks, p-rules…

Artificial Intelligence · Computer Science 2022-09-02 Xiuyi Fan

This work advances and substantiates the thesis that the resolution of this crisis lies in the domain of possibility theory, specifically in the axiomatic approach developed in Bychkovs article. Unlike numerous attempts to fix Dempster…

Artificial Intelligence · Computer Science 2025-12-08 Bychkov Oleksii , Bychkova Sophia , Lytvynchuk Khrystyna