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Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel…

Computation and Language · Computer Science 2024-06-03 Rongwu Xu , Zehan Qi , Wei Xu

This position paper proposes a fundamental shift in designing code generation models: treating reasoning depth as a controllable resource. Rather than being an incidental byproduct of prompting, we argue that the trade-off between rapid,…

Software Engineering · Computer Science 2025-06-12 Zongjie Li , Shuai Wang

Inspired by e-participation systems, in this paper we propose a new model to represent human debates and methods to obtain collective conclusions from them. This model overcomes drawbacks of existing approaches by allowing users to…

Artificial Intelligence · Computer Science 2020-07-15 Jordi Ganzer , Natalia Criado , Maite Lopez-Sanchez , Simon Parsons , Juan A. Rodriguez-Aguilar

This paper studies temporal planning in probabilistic environments, modeled as labeled Markov decision processes (MDPs), with user preferences over multiple temporal goals. Existing works reflect such preferences as a prioritized list of…

Formal Languages and Automata Theory · Computer Science 2023-04-25 Lening Li , Hazhar Rahmani , Jie Fu

The computational properties of modal and propositional dependence logics have been extensively studied over the past few years, starting from a result by Sevenster showing NEXPTIME-completeness of the satisfiability problem for modal…

Logic in Computer Science · Computer Science 2023-06-22 Miika Hannula

We introduce a logic for reasoning about evidence, that essentially views evidence as a function from prior beliefs (before making an observation) to posterior beliefs (after making the observation). We provide a sound and complete…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern , Riccardo Pucella

We present and analyze a natural hierarchy of weak theories, develop analysis in them, and show that they are interpretable in bounded quantifier arithmetic $\text{I}\Delta_0$ (and hence in Robinson arithmetic Q). The strongest theories…

Logic · Mathematics 2016-12-20 Dmytro Taranovsky

In this paper we present an alternative approach to formalize the theory of logic programming. In this formalization we allow existential quantified variables and equations in queries. In opposite to standard approaches the role of answer…

Logic in Computer Science · Computer Science 2022-07-20 Ján Komara

Epistemic logic programs constitute an extension of the stable models semantics to deal with new constructs called subjective literals. Informally speaking, a subjective literal allows checking whether some regular literal is true in all…

Artificial Intelligence · Computer Science 2021-07-01 Pedro Cabalar , Jorge Fandinno , Luis Fariñas del Cerro

Counterfactual decision-making in the face of uncertainty involves selecting the optimal action from several alternatives using causal reasoning. Decision-makers often rank expected potential outcomes (or their corresponding utility and…

Artificial Intelligence · Computer Science 2025-11-17 Yuta Kawakami , Jin Tian

Motivated by the problem of finding finite versions of classical incompleteness theorems, we present some conjectures that go beyond ${\bf NP\neq co NP}$. These conjectures formally connect computational complexity with the difficulty of…

Logic · Mathematics 2017-05-22 Pavel Pudlak

Pervasive cross-section dependence is increasingly recognized as a characteristic of economic data and the approximate factor model provides a useful framework for analysis. Assuming a strong factor structure where $\Lop\Lo/N^\alpha$ is…

Econometrics · Economics 2023-03-07 Jushan Bai , Serena Ng

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data…

Logic in Computer Science · Computer Science 2014-01-08 Paulo Shakarian , Gerardo I. Simari , Marcelo A. Falappa

The outcome of a weak quantum measurement conditioned to a subsequent postselection (a weak value protocol) can assume peculiar values. These results cannot be explained in terms of conditional probabilistic outcomes of projective…

Quantum Physics · Physics 2016-05-31 Alessandro Romito , Andrew N. Jordan , Yakir Aharonov , Yuval Gefen

Despite the growing demand for eliciting uncertainty from large language models (LLMs), empirical evidence suggests that LLM behavior is not always adequately captured by the elicitation techniques developed under the classical…

Artificial Intelligence · Computer Science 2026-03-12 Anita Yang , Krikamol Muandet , Michele Caprio , Siu Lun Chau , Masaki Adachi

Latent reasoning represents a new development in Transformer language models that has shown potential in compressing reasoning lengths compared to chain-of-thought reasoning. By directly passing the information-rich previous final latent…

Machine Learning · Computer Science 2025-11-27 Alex Ning , Yen-Ling Kuo , Gabe Gomes

In this study, we study weak values from a quantum-logical viewpoint. In addition, we examine the validity of the counterfactual statements of Hardy's paradox, which are based on weak values, and we show that these statements have not been…

Quantum Physics · Physics 2013-07-23 Riuji Mochizuki

We study the computational expressivity of proof systems with fixed point operators, within the 'proofs-as-programs' paradigm. We start with a calculus muLJ (due to Clairambault) that extends intuitionistic logic by least and greatest…

Logic in Computer Science · Computer Science 2025-11-05 Gianluca Curzi , Anupam Das

In this work, we present a logical formalism for reasoning about quantum systems in finite dimension. Contrary to the usual approach in quantum logic, our formalism is based classical first-order logic, which allows us to use the tools of…

Quantum Physics · Physics 2026-02-19 Olivier Brunet

As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing…

Machine Learning · Computer Science 2020-11-13 Himabindu Lakkaraju , Nino Arsov , Osbert Bastani
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