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Book Synopsis

.- Enhancing Personalized Nutrition: A Hybrid Intelligence Approach with LLM-Powered Meal Planning.

.- Generating Explanations for Molecular Property Predictions in Graph Neural Networks.

.- Balancing (Normative) Reasons for the Intelligent Human-input-based Blockchain Oracle.

.- Feature Generation Using LLMs: An Evolutionary Algorithm Approach.

.- Augmenting Dark Patterns Text Data by Leveraging Large Language Models: a Multi-Agent Framework and Parameter-Efficient Fine-Tuning.

.- Assessing the Robustness of LLMs in Predicting Supports and Attacks.

.- Enhancing accuracy and explainability in anomaly classification with large language models.

.- Agent-Based Hate Speech Moderation Approach.

Advances in explainability agents and large language models

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    Order before 4pm tomorrow for delivery by Wed 17 Jun 2026.

    A Paperback by Yazan Mualla

    15 in stock


      View other formats and editions of Advances in explainability agents and large language models by Yazan Mualla

      Publisher: Springer
      Publication Date: 30/05/2025
      ISBN13: 9783031891021, 978-3031891021
      ISBN10:
      Also in:
      Computing Computer science

      Description

      Book Synopsis

      .- Enhancing Personalized Nutrition: A Hybrid Intelligence Approach with LLM-Powered Meal Planning.

      .- Generating Explanations for Molecular Property Predictions in Graph Neural Networks.

      .- Balancing (Normative) Reasons for the Intelligent Human-input-based Blockchain Oracle.

      .- Feature Generation Using LLMs: An Evolutionary Algorithm Approach.

      .- Augmenting Dark Patterns Text Data by Leveraging Large Language Models: a Multi-Agent Framework and Parameter-Efficient Fine-Tuning.

      .- Assessing the Robustness of LLMs in Predicting Supports and Attacks.

      .- Enhancing accuracy and explainability in anomaly classification with large language models.

      .- Agent-Based Hate Speech Moderation Approach.

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