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Large language models (LLMs) are increasingly used as raters for evaluation tasks. However, their reliability is often limited for subjective tasks, when human judgments involve subtle reasoning beyond annotation labels. Thinking traces,…

Artificial Intelligence · Computer Science 2026-02-23 Xingjian Zhang , Tianhong Gao , Suliang Jin , Tianhao Wang , Teng Ye , Eytan Adar , Qiaozhu Mei

We study local consequence relations in modal extensions of product logic over Kripke models with either valued (fuzzy) or crisp accessibility relations. In both settings, we consider semantics over the full class of product algebras as…

Logic · Mathematics 2026-05-15 Amanda Vidal

In supervised learning, obtaining a large set of fully-labeled training data is expensive. We show that we do not always need full label information on every single training example to train a competent classifier. Specifically, inspired by…

Machine Learning · Computer Science 2023-01-18 Shiyu Duan , Spencer Chang , Jose C. Principe

We give a semantics for the lambda-calculus based on a topological duality theorem in nominal sets. A novel interpretation of lambda is given in terms of adjoints, and lambda-terms are interpreted absolutely as sets (no valuation is…

Logic in Computer Science · Computer Science 2016-10-07 Murdoch J. Gabbay , Michael J. Gabbay

We investigate the decidability of the definability problem for fragments of first order logic over finite words enriched with modular predicates. Our approach aims toward the most generic statements that we could achieve, which…

Logic in Computer Science · Computer Science 2015-11-16 Luc Dartois , Charles Paperman

The ability of Large Language Models (LLMs) to perform reasoning tasks such as deduction has been widely investigated in recent years. Yet, their capacity to generate proofs-faithful, human-readable explanations of why conclusions…

Artificial Intelligence · Computer Science 2026-01-21 Hui Yang , Jiaoyan Chen , Uli Sattler

We introduce a family of comparative plausibility logics over neighbourhood models, generalising Lewis' comparative plausibility operator over sphere models. We provide axiom systems for the logics, and prove their soundness and…

Logic in Computer Science · Computer Science 2022-10-20 Tiziano Dalmonte , Marianna Girlando

We introduce generative interpretation, a new approach to estimating contractual meaning using large language models. As AI triumphalism is the order of the day, we proceed by way of grounded case studies, each illustrating the capabilities…

Computation and Language · Computer Science 2023-08-15 Yonathan A. Arbel , David Hoffman

For every class $\mathscr{C}$ of word languages, one may associate a decision problem called $\mathscr{C}$-separation. Given two regular languages, it asks whether there exists a third language in $\mathscr{C}$ containing the first…

Logic in Computer Science · Computer Science 2023-06-22 Thomas Place , Varun Ramanathan , Pascal Weil

In this paper, we introduce a novel team semantics of LTL inspired by inquisitive logic. The main features of the resulting logic, we call InqLTL, are the intuitionistic interpretation of implication and the Boolean semantics of…

Logic in Computer Science · Computer Science 2025-05-19 Laura Bozzelli , Tadeusz Litak , Munyque Mittelmann , Aniello Murano

Using recent results in topos theory, two systems of higher-order logic are shown to be complete with respect to sheaf models over topological spaces---so-called ``topological semantics''. The first is classical higher-order logic, with…

Logic · Mathematics 2023-03-31 Steve Awodey , Carsten Butz

We define a semantics for Milner's pi-calculus, with three main novelties. First, it provides a fully-abstract model for fair testing equivalence, whereas previous semantics covered variants of bisimilarity and the may and must testing…

Logic in Computer Science · Computer Science 2013-10-17 Clovis Eberhart , Tom Hirschowitz , Thomas Seiller

The task of multi-label learning is to predict a set of relevant labels for the unseen instance. Traditional multi-label learning algorithms treat each class label as a logical indicator of whether the corresponding label is relevant or…

Machine Learning · Computer Science 2019-04-17 Ruifeng Shao , Ning Xu , Xin Geng

Semantic role labeling is primarily used to identify predicates, arguments, and their semantic relationships. Due to the limitations of modeling methods and the conditions of pre-identified predicates, previous work has focused on the…

Computation and Language · Computer Science 2020-10-12 Zuchao Li , Hai Zhao , Rui Wang , Kevin Parnow

Given a regular cardinal $\kappa$ such that $\kappa^{<\kappa}=\kappa$ (e.g., if the Generalized Continuum Hypothesis holds), we develop a proof system for classical infinitary logic that includes heterogeneous quantification (i.e., infinite…

Logic · Mathematics 2019-02-04 Christian Espíndola

Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space, thus raising the question: is it the case that one of these approaches is superior to the…

Computation and Language · Computer Science 2020-11-17 António Branco , João Rodrigues , Małgorzata Salawa , Ruben Branco , Chakaveh Saedi

Recent breakthroughs in NLP research, such as the advent of Transformer models have indisputably contributed to major advancements in several tasks. However, few works research robustness and explainability issues of their evaluation…

Computation and Language · Computer Science 2022-10-31 Maria Lymperaiou , George Manoliadis , Orfeas Menis Mastromichalakis , Edmund G. Dervakos , Giorgos Stamou

Incomplete relevance judgments limit the re-usability of test collections. When new systems are compared against previous systems used to build the pool of judged documents, they often do so at a disadvantage due to the ``holes'' in test…

Information Retrieval · Computer Science 2024-05-10 Zahra Abbasiantaeb , Chuan Meng , Leif Azzopardi , Mohammad Aliannejadi

Do LMs infer the semantics of text from co-occurrence patterns in their training data? Merrill et al. (2022) argue that, in theory, sentence co-occurrence probabilities predicted by an optimal LM should reflect the entailment relationship…

Computation and Language · Computer Science 2024-07-18 William Merrill , Zhaofeng Wu , Norihito Naka , Yoon Kim , Tal Linzen

In this paper, we study a new Kripke-style semantics for classical modal logic, named as provability models. We study provability models for the propositional modal logics K, K4, S4 GL, GLP and the interpretability logic ILM. Provability…

Logic · Mathematics 2025-11-20 Mojtaba Mojtahedi , Borja Sierra Miranda
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