1 option
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 / edited by Yazan Mualla, Liuwen Yu, Davide Liga, Igor Tchappi, Réka Markovich.
Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online
View online- Format:
- Book
- Series:
- Communications in Computer and Information Science, 1865-0937 ; 2471
- Language:
- English
- Subjects (All):
- Computer science.
- Computer Science.
- Local Subjects:
- Computer Science.
- Physical Description:
- 1 online resource (IX, 127 p. 37 illus., 29 illus. in color.)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
- Summary:
- 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).
- Contents:
- 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.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-031-89103-1
- OCLC:
- 1517961247
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.