1 citations · 2 across the 5 of their papers we have counts for
5 papers
Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications
Yvon K. Awuklu, Meghyn Bienvenu, Katsumi Inoue +2
In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge. Our framework employs logi…
Complexity of Abduction in Łukasiewicz Logic
Katsumi Inoue, Daniil Kozhemiachenko
We explore the problem of explaining observations in contexts involving statements with truth degrees such as `the lift is loaded', `the symptoms are severe', etc. To formalise the…
A Rule-Based Approach to Specifying Preferences over Conflicting Facts and Querying Inconsistent Knowledge Bases
Meghyn Bienvenu, Camille Bourgaux, Katsumi Inoue +1
Repair-based semantics have been extensively studied as a means of obtaining meaningful answers to queries posed over inconsistent knowledge bases (KBs). While several works have c…
Neuro-Symbolic Contrastive Learning for Cross-domain Inference
Mingyue Liu, Ryo Ueda, Zhen Wan +2
Pre-trained language models (PLMs) have made significant advances in natural language inference (NLI) tasks, however their sensitivity to textual perturbations and dependence on la…
Abductive Reasoning in a Paraconsistent Framework
Meghyn Bienvenu, Katsumi Inoue, Daniil Kozhemiachenko
We explore the problem of explaining observations starting from a classically inconsistent theory by adopting a paraconsistent framework. We consider two expansions of the well-kno…