Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL

• URL: http://arxiv.org/abs/2302.13187v1
• Date: Sat, 25 Feb 2023 22:59:04 GMT
• Title: Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL
• Authors: Luc\'ia G\'omez \'Alvarez, Sebastian Rudolph and Hannes Strass
• Abstract summary: We introduce Standpoint EL, a multi-modal extension of EL that allows for the integrated representation of domain knowledge. We establish that Standpoint EL's favourable PTime standard reasoning, whereas introducing additional roles like empty standpoints makes standard reasoning intractable.
• Score: 2.9005223064604073
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The tractability of the lightweight description logic EL has allowed for the construction of large and widely used ontologies that support semantic interoperability. However, comprehensive domains with a broad user base are often at odds with strong axiomatisations otherwise useful for inferencing, since these are usually context-dependent and subject to diverging perspectives. In this paper we introduce Standpoint EL, a multi-modal extension of EL that allows for the integrated representation of domain knowledge relative to diverse, possibly conflicting standpoints (or contexts), which can be hierarchically organised and put in relation to each other. We establish that Standpoint EL still exhibits EL's favourable PTime standard reasoning, whereas introducing additional features like empty standpoints, rigid roles, and nominals makes standard reasoning tasks intractable.

Related papers

• Hints of Prompt: Enhancing Visual Representation for Multimodal LLMs in Autonomous Driving [65.04643267731122]
  General MLLMs combined with CLIP often struggle to represent driving-specific scenarios accurately. We propose the Hints of Prompt (HoP) framework, which introduces three key enhancements. These hints are fused through a Hint Fusion module, enriching visual representations and enhancing multimodal reasoning.
  arXiv  Detail & Related papers  (2024-11-20T06:58:33Z)
• Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts [49.950419707905944]
  We present Self-MoE, an approach that transforms a monolithic LLM into a compositional, modular system of self-specialized experts. Our approach leverages self-specialization, which constructs expert modules using self-generated synthetic data. Our findings highlight the critical role of modularity, the applicability of Self-MoE to multiple base LLMs, and the potential of self-improvement in achieving efficient, scalable, and adaptable systems.
  arXiv  Detail & Related papers  (2024-06-17T19:06:54Z)
• Cantor: Inspiring Multimodal Chain-of-Thought of MLLM [83.6663322930814]
  We argue that converging visual context acquisition and logical reasoning is pivotal for tackling visual reasoning tasks. We propose an innovative multimodal CoT framework, termed Cantor, characterized by a perception-decision architecture. Our experiments demonstrate the efficacy of the proposed framework, showing significant improvements in multimodal CoT performance.
  arXiv  Detail & Related papers  (2024-04-24T17:59:48Z)
• BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models [13.229325187638432]
  Large language models (LLMs) call for extension of context to handle many critical applications. Existing approaches are prone to expensive costs and inferior quality of context extension. Extensible embedding stand as an enhancement of typical token embedding.
  arXiv  Detail & Related papers  (2024-02-18T12:41:01Z)
• LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model [54.850048630298495]
  We introduce LISA++, an update to the existing LISA model, focusing on improving core functionalities while keeping the base architecture intact. The instance segmentation ability has been added, providing a more detailed scene analysis along with the existing multi-region semantic segmentation. These improvements are achieved by curating existing samples of generic segmentation datasets aimed specifically at enhancing the segmentation and conversational skills without structural change and additional data sources.
  arXiv  Detail & Related papers  (2023-12-28T18:58:33Z)
• A Principled Framework for Knowledge-enhanced Large Language Model [58.1536118111993]
  Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning. This paper introduces a rigorously designed framework for creating LLMs that effectively anchor knowledge and employ a closed-loop reasoning process.
  arXiv  Detail & Related papers  (2023-11-18T18:10:02Z)
• A Semantic Approach to Decidability in Epistemic Planning (Extended Version) [72.77805489645604]
  We use a novel semantic approach to achieve decidability. Specifically, we augment the logic of knowledge S5$_n$ and with an interaction axiom called (knowledge) commutativity. We prove that our framework admits a finitary non-fixpoint characterization of common knowledge, which is of independent interest.
  arXiv  Detail & Related papers  (2023-07-28T11:26:26Z)
• Pushing the Boundaries of Tractable Multiperspective Reasoning: A Deduction Calculus for Standpoint EL+ [2.9005223064604073]
  Standpoint EL is a multi-modal extension of the popular description logic EL. In this paper, we show that we can push the expressivity of this formalism, arriving at an extended logic, called Standpoint EL+. This is achieved by designing a prototypical satisfiability-checking deduction calculus.
  arXiv  Detail & Related papers  (2023-04-27T16:49:17Z)
• Standpoint Linear Temporal Logic [2.552459629685159]
  We present standpoint linear temporal logic (SLTL), a new logic that combines the temporal features of thepective with the multi-perspective modelling capacity of SL. We define the logic SLTL, its syntax, and its semantics, establish its decidability and terminating complexity, and provide a tableau calculus to automate SLTL reasoning.
  arXiv  Detail & Related papers  (2023-04-27T15:03:38Z)
• How to Agree to Disagree: Managing Ontological Perspectives using Standpoint Logic [2.9005223064604073]
  Standpoint Logic is a simple, yet versatile multi-modal logic add-on'' for existing KR languages. We provide a polytime translation into the standpoint-free version of First-Order Standpoint Logic. We then establish a similar translation for the very expressive description logic SROIQb_s underlying the OWL 2 DL language.
  arXiv  Detail & Related papers  (2022-06-14T12:29:08Z)
• Strong Admissibility for Abstract Dialectical Frameworks [0.0]
  We present the concept of strong admissibility of interpretations for ADFs. We show that strongly admissible interpretations of ADFs form a lattice with the grounded interpretation as top element.
  arXiv  Detail & Related papers  (2020-12-10T21:50:35Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.