International Workshop on Generative AI & Trustworthy Large Language Models: Ensuring Trust and Security (GAIT 2024)

Description

GAIT workshop addresses the requirement of instilling trust and security in the rapidly evolving domain of generative AI and large language models (LLMs). In the age of advanced artificial intelligence, the development and deployment of generative models raise critical questions about trustworthiness, security, and ethical use. GAIT workshop will explore the forefront of research and practice in creating LLMs that are secure, reliable, and aligned with ethical standards. We invite studies discussing strategies for enhancing transparency, accountability, and fairness in AI systems. Participants will engage with topics such as data privacy, bias detection and mitigation, and the secure implementation of AI technologies in sensitive environments. GAIT workshop is intended for researchers and technologists dedicated to advancing the field of generative AI while ensuring the technology is developed and utilized in a manner that earns the trust and ensures the security of all stakeholders.

Topics

The list of topics includes, but is not limited to:

• Security and Privacy in Generative AI
  Papers in this area deal with the security challenges specific to generative AI, including adversarial attacks, data encryption, and privacy-preserving techniques in development.
• Advancements in LLM Architectures
  Papers in this area deal with the latest developments in secure and scalable architectures for LLMs, focusing on design and implementation strategies.
• Generative AI in Content Integrity and Authentication
  Papers in this area deal with ensuring the authenticity of AI-generated content, addressing challenges in detecting and preventing misuse.
• Ethical Frameworks and Trust in Generative AI
  Papers in this area deal with ethical considerations, bias and fairness, building trust, and the development of ethical frameworks specific to generative applications.
• Data Handling for Generative AI
  Papers in this area deal with data selection, preprocessing for LLM training, overcoming data bias, and ensuring diversity in training sets.
• Optimization Strategies for LLMs
  Papers in this area deal with adaptive learning rates, optimization strategies, and techniques for efficient large-scale model training.
• Innovative Training Techniques for LLMs
  Papers in this area deal with curriculum learning, sequential training techniques, and strategies for reducing the environmental impact of LLM training.
• Model Evaluation and Benchmarking in LLMs
  Papers in this area deal with post-training evaluation, benchmarking methods, and ethical considerations in fine-tuning generative models.
• Regulatory and Policy Considerations for LLMs
  Papers in this area deal with the regulatory landscape, policy considerations, and the role of human oversight in the development and deployment of LLMs.
• Generative AI in Sensitive Environments
  Papers in this area deal with the secure deployment of generative AI systems in sensitive or regulated environments, including IoT and edge computing, with a focus on security protocols and emerging threats.
• Software Engineering and Generative AI
  Papers in this area deal with integrating generative AI technologies into software engineering practices, focusing on automating code generation, improving software design and testing, and enhancing development workflows.

Submission

Authors are invited to submit original unpublished research papers as well as industrial practice papers. Simultaneous submissions to other conferences are not permitted. Detailed instructions for electronic paper submission, panel proposals, and review process can be found at QRS submission.

Each submission can have a maximum of ten pages. It should include a title, the name and affiliation of each author, a 300-word abstract, and up to 6 keywords. Shorter version papers (up to six pages) are also allowed.

All papers must conform to the QRS conference proceedings format (PDF | Word DOCX | Latex) and Submission Guideline set in advance by QRS 2024. At least one of the authors of each accepted paper is required to pay the full registration fee and present the paper at the workshop. Submissions must be in PDF format and uploaded to the conference submission site. Arrangements are being made to publish extended version of top-quality papers in selected SCI journals.

Organizational Chairs

Pekka Abrahamsson

Tampere University, Finland

Tapio Frantti

University of Jyväskylä, Finland

Program Committee