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Related papers: Chase's lemma and its context

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In many expert and everyday reasoning contexts it is very useful to reason on the basis of defeasible assumptions. For instance, if the information at hand is incomplete we often use plausible assumptions, or if the information is…

Logic in Computer Science · Computer Science 2018-04-25 AnneMarie Borg

Citation texts are sometimes not very informative or in some cases inaccurate by themselves; they need the appropriate context from the referenced paper to reflect its exact contributions. To address this problem, we propose an unsupervised…

Computation and Language · Computer Science 2017-05-24 Arman Cohan , Nazli Goharian

Motivation: Sequence mapping is the cornerstone of modern genomics. However, most existing sequence mapping algorithms are insufficiently general. Results: We introduce context schemes: a method that allows the unambiguous recognition of a…

Genomics · Quantitative Biology 2015-08-28 Adam Novak , Yohei Rosen , David Haussler , Benedict Paten

Explainability of a classification model is crucial when deployed in real-world decision support systems. Explanations make predictions actionable to the user and should inform about the capabilities and limitations of the system. Existing…

Machine Learning · Computer Science 2022-12-13 Erwin Walraven , Ajaya Adhikari , Cor J. Veenman

As data grows in size and complexity, finding frameworks which aid in interpretation and analysis has become critical. This is particularly true when data comes from complex systems where extensive structure is available, but must be drawn…

Machine Learning · Computer Science 2021-05-24 Henry Kvinge , Brett Jefferson , Cliff Joslyn , Emilie Purvine

Messages often refer to entities such as people, places and events. Correct identification of the intended reference is an essential part of communication. Lack of shared unique names often complicates entity reference. Shared knowledge can…

Computation and Language · Computer Science 2017-10-31 Ramanathan V Guha , Vineet Gupta

Large language models (LLMs) are increasingly used to generate software artifacts, such as source code, tests, and trace links. Requirements play a central role in shaping the input prompts that guide LLMs, as they are often used as part of…

Software Engineering · Computer Science 2025-01-10 Andreas Vogelsang , Alexander Korn , Giovanna Broccia , Alessio Ferrari , Jannik Fischbach , Chetan Arora

Conditional acceptability refers to how plausible a conditional statement is perceived to be. It plays an important role in communication and reasoning, as it influences how individuals interpret implications, assess arguments, and make…

Computation and Language · Computer Science 2026-03-20 Jasmin Orth , Philipp Mondorf , Barbara Plank

In formal language theory, one of the most fundamental tools, known as pumping lemmas, is extremely useful for regular and context-free languages. However, there are natural properties for which the pumping lemmas are of little use. One of…

Computational Complexity · Computer Science 2009-03-05 Tomoyuki Yamakami

Trace semantics has been defined for various kinds of state-based systems, notably with different forms of branching such as non-determinism vs. probability. In this paper we claim to identify one underlying mathematical structure behind…

Logic in Computer Science · Computer Science 2015-07-01 Ichiro Hasuo , Bart Jacobs , Ana Sokolova

In this paper we review the concepts of Bayesian evidence and Bayes factors, also known as log odds ratios, and their application to model selection. The theory is presented along with a discussion of analytic, approximate and numerical…

Methodology · Statistics 2015-11-24 Kevin H. Knuth , Michael Habeck , Nabin K. Malakar , Asim M. Mubeen , Ben Placek

A modelling language is described which is suitable for the correlation of information when the underlying functional model of the system is incomplete or uncertain and the temporal dependencies are imprecise. An efficient and incremental…

Artificial Intelligence · Computer Science 2013-02-08 John Bigham

The Shapley value has become a popular method to attribute the prediction of a machine-learning model on an input to its base features. The use of the Shapley value is justified by citing [16] showing that it is the \emph{unique} method…

Artificial Intelligence · Computer Science 2020-02-10 Mukund Sundararajan , Amir Najmi

We investigate multi-label classification involving large sets of labels, where the output labels may be known to satisfy some logical constraints. We look at an architecture in which classifiers for individual labels are fed into an…

Machine Learning · Computer Science 2025-07-22 Mykhailo Buleshnyi , Anna Polova , Zsolt Zombori , Michael Benedikt

Pumping lemmas are created to prove that given languages are not belong to certain language classes. There are several known pumping lemmas for the whole class and some special classes of the context-free languages. In this paper we prove…

Formal Languages and Automata Theory · Computer Science 2010-12-02 Géza Horváth , Benedek Nagy

Calibration is a frequently invoked concept when useful label probability estimates are required on top of classification accuracy. A calibrated model is a function whose values correctly reflect underlying label probabilities. Calibration…

Machine Learning · Computer Science 2024-12-03 Alireza Torabian , Ruth Urner

It is well known that in quantum mechanics we cannot always define consistently properties that are context independent. Many approaches exist to describe contextual properties, such as Contextuality by Default (CbD), sheaf theory, topos…

Quantum Physics · Physics 2017-07-18 J. Acacio de Barros , Federico Holik , Decio Krause

In materials science and engineering, one is typically searching for materials that exhibit exceptional performance for a certain function, and the number of these materials is extremely small. Thus, statistically speaking, we are…

Materials Science · Physics 2021-04-06 Mario Boley , Matthias Scheffler

While training models and labeling data are resource-intensive, a wealth of pre-trained models and unlabeled data exists. To effectively utilize these resources, we present an approach to actively select pre-trained models while minimizing…

Machine Learning · Computer Science 2025-02-11 Xuefeng Liu , Fangfang Xia , Rick L. Stevens , Yuxin Chen

We present the second generation of a rule-based language called Biochemical Space Language (BCSL) that combines the advantages of different approaches and thus makes an effort to overcome several problems with existing solutions. The key…

Molecular Networks · Quantitative Biology 2021-01-27 Matej Troják , David Šafránek , Luboš Brim