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Advances in explainability, agents, ...

CALM (Workshop) (2024 :)

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Advances in explainability, agents, and large language models = first International Workshop on Causality, Agents and Large Models, CALM 2024, Kyoto, Japan, November 18-19, 2024 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in explainability, agents, and large language models/ edited by Yazan Mualla ... [et al.].
Reminder of title:	first International Workshop on Causality, Agents and Large Models, CALM 2024, Kyoto, Japan, November 18-19, 2024 : proceedings /
remainder title:	CALM 2024
other author:	Mualla, Yazan.
corporate name:	CALM (Workshop)
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	ix, 127 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Intelligent agents (Computer software) - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-89103-8
ISBN:	9783031891038

Advances in explainability, agents, and large language models = first International Workshop on Causality, Agents and Large Models, CALM 2024, Kyoto, Japan, November 18-19, 2024 : proceedings /
Advances in explainability, agents, and large language modelsfirst International Workshop on Causality, Agents and Large Models, CALM 2024, Kyoto, Japan, November 18-19, 2024 : proceedings /[electronic resource] :CALM 2024edited by Yazan Mualla ... [et al.]. - Cham :Springer Nature Switzerland :2025. - ix, 127 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,24711865-0937 ;. - Communications in computer and information science ;2471..

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.

This book constitutes the refereed proceedings of the First International Workshop on Advances in explainability, agents, and large language models, CALM 2024, held in Kyoto, Japan, during November 18-19, 2024. The 7 full papers and 1 short paper presented in this book were carefully reviewed and selected from 17 submissions. The Workshop on Causality, Agents, and Large Models (CALM) was established to foster interdisciplinary collaboration and advance research at the intersection of causal reasoning, multi-agent systems (MAS), and large language models (LLMs).

ISBN: 9783031891038

Standard No.: 10.1007/978-3-031-89103-8doiSubjects--Topical Terms:

582135
Intelligent agents (Computer software)
--Congresses.

LC Class. No.: QA76.76.I58

Dewey Class. No.: 006.30285436

Advances in explainability, agents, and large language models = first International Workshop on Causality, Agents and Large Models, CALM 2024, Kyoto, Japan, November 18-19, 2024 : proceedings /
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