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Related papers: Dialectic Reasoning with Inconsistent Information

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In real-world scenarios, typical visual recognition systems could fail under two major causes, i.e., the misclassification between known classes and the excusable misbehavior on unknown-class images. To tackle these deficiencies, flexible…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Lei Fan , Bo Liu , Haoxiang Li , Ying Wu , Gang Hua

We propose a general framework for inconsistency-tolerant query answering within existential rule setting. This framework unifies the main semantics proposed by the state of art and introduces new ones based on cardinality and majority…

Artificial Intelligence · Computer Science 2016-02-19 Jean Francois Baget , Salem Benferhat , Zied Bouraoui , Madalina Croitoru , Marie-Laure Mugnier , Odile Papini , Swan Rocher , Karim Tabia

Argumentation theory is a powerful paradigm that formalizes a type of commonsense reasoning that aims to simulate the human ability to resolve a specific problem in an intelligent manner. A classical argumentation process takes into account…

Artificial Intelligence · Computer Science 2019-03-06 Maximiliano C. D. Budán , Gerardo I. Simari , Ignacio Viglizzo , Guillermo R. Simari

Consistent answers to a query from a possibly inconsistent database are answers that are simultaneously retrieved from every possible repair of the database. Repairs are consistent instances that minimally differ from the original…

Databases · Computer Science 2021-10-20 Leopoldo Bertossi

Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Riccardo Pucella

In today's multilingual lexical databases, the majority of the world's languages are under-represented. Beyond a mere issue of resource incompleteness, we show that existing lexical databases have structural limitations that result in a…

Computation and Language · Computer Science 2023-01-24 Fausto Giunchiglia , Gabor Bella , Nandu Chandran Nair , Yang Chi , Hao Xu

Information accounting provides a better foundation for hypothesis testing than does uncertainty quantification. A quantitative account of science is derived under this perspective that alleviates the need for epistemic bridge principles,…

Other Statistics · Statistics 2017-04-26 Grey Nearing , Hoshin Gupta

This paper describes an approach to the automatic identification of lexical information in on-line dictionaries. This approach uses bootstrapping techniques, specifically so that ambiguity in the dictionary text can be treated properly.…

cmp-lg · Computer Science 2008-02-03 Lucy Vanderwende

We investigate how disagreement in natural language inference (NLI) annotation arises. We developed a taxonomy of disagreement sources with 10 categories spanning 3 high-level classes. We found that some disagreements are due to uncertainty…

Computation and Language · Computer Science 2022-09-09 Nan-Jiang Jiang , Marie-Catherine de Marneffe

For a newcomer, paraconsistent logics can be difficult to grasp. Even experts in logic can find the concept of paraconsistency to be suspicious or misguided, if not actually wrong. The problem is that although they usually have much in…

Logic · Mathematics 2013-12-17 Jesse Alama

An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained…

Artificial Intelligence · Computer Science 2020-02-19 Claudia Schulz , Francesca Toni

Reliable Large Language Models (LLMs) should abstain when confidence is insufficient. However, prior studies often treat refusal as a generic "I don't know'', failing to distinguish input-level ambiguity (data uncertainty) from capability…

Computation and Language · Computer Science 2026-04-21 Jingyi Ren , Ante Wang , Yunghwei Lai , Xiaolong Wang , Linlu Gong , Weitao Li , Weizhi Ma , Yang Liu

Understanding why a large language model (LLM) is uncertain about the response is important for their reliable deployment. Current approaches, which either provide a single uncertainty score or rely on the classical aleatoric-epistemic…

Artificial Intelligence · Computer Science 2026-03-27 Aditya Taparia , Ransalu Senanayake , Kowshik Thopalli , Vivek Narayanaswamy

Justification theory is a unifying framework for semantics of non-monotonic logics. It is built on the notion of a justification, which intuitively is a graph that explains the truth value of certain facts in a structure. Knowledge…

Logic in Computer Science · Computer Science 2019-05-16 Simon Marynissen

This paper considers the challenges Large Language Models (LLMs) face when reasoning over text that includes information involving uncertainty explicitly quantified via probability values. This type of reasoning is relevant to a variety of…

Computation and Language · Computer Science 2024-12-30 Aliakbar Nafar , Kristen Brent Venable , Parisa Kordjamshidi

As large language models continue to be widely developed, robust uncertainty quantification techniques will become crucial for their safe deployment in high-stakes scenarios. In this work, we explore how conformal prediction can be used to…

Computation and Language · Computer Science 2023-07-11 Bhawesh Kumar , Charlie Lu , Gauri Gupta , Anil Palepu , David Bellamy , Ramesh Raskar , Andrew Beam

Separation Logic is a widely used formalism for describing dynamically allocated linked data structures, such as lists, trees, etc. The decidability status of various fragments of the logic constitutes a long standing open problem. Current…

Logic in Computer Science · Computer Science 2013-04-02 Radu Iosif , Adam Rogalewicz , Jiri Simacek

The paper describes an extension of well-founded semantics for logic programs with two types of negation. In this extension information about preferences between rules can be expressed in the logical language and derived dynamically. This…

Artificial Intelligence · Computer Science 2008-02-03 G. Brewka

Diagnostic reasoning has been characterized logically as consistency-based reasoning or abductive reasoning. Previous analyses in the literature have shown, on the one hand, that choosing the (in general more restrictive) abductive…

Artificial Intelligence · Computer Science 2007-05-23 Daniele Theseider Dupre'

A gradual semantics takes a weighted argumentation framework as input and outputs a final acceptability degree for each argument, with different semantics performing the computation in different manners. In this work, we consider the…

Artificial Intelligence · Computer Science 2023-02-09 Nir Oren , Bruno Yun