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Image-text coherence and its implications for multimodal AI.

Malihe Alikhani1, Baber Khalid2, Matthew Stone2

  • 1Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, United States.

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Summary
This summary is machine-generated.

This study introduces coherence relations to model image-text presentations in AI. This approach offers a robust framework for understanding communicative goals in multimodal AI systems.

Keywords:
coherencediscourseevaluationmachine learningmultimodality

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Area of Science:

  • Artificial Intelligence
  • Computational Linguistics
  • Human-Computer Interaction

Background:

  • Human communication frequently integrates images and text, particularly in online environments.
  • Existing frameworks for image-text analysis often focus on information overlap or relevance.
  • Coherence theory offers an alternative perspective by examining pragmatic relations between discourse units.

Purpose of the Study:

  • To demonstrate the utility of image-text coherence relations for modeling pragmatic aspects of AI presentations.
  • To present coherence theory as a robust and effective abstraction for communicative goals in AI systems.
  • To explore applications of coherence in image-text data analysis and AI tasks.

Main Methods:

  • Reviewing case studies of coherence in image-text datasets.
  • Investigating coherence prediction from limited annotations (few-shot learning).
  • Developing coherence models for AI tasks like image caption generation and evaluation.

Main Results:

  • Coherence theory provides a simplified and effective abstraction for communicative goals.
  • The framework is applicable to various image-text tasks, including captioning and evaluation.
  • Coherence relations can be predicted from minimal data, enhancing AI model efficiency.

Conclusions:

  • Image-text coherence relations offer a powerful tool for understanding and modeling multimodal communication in AI.
  • This approach enhances the pragmatic capabilities of AI systems dealing with integrated imagery and text.
  • Coherence theory presents a scalable and effective method for developing more sophisticated AI communication systems.