View Proposal

---

Proposer

Radu-Casian Mihailescu

Title

Efficient training techniques for fine-tuning LLMs to domain-specific applications

Goal

Description

Fine-tuning LLMs involves adapting a pre-trained model for a specific downstream task, with applications to various domains such as medical, financial, educational, or legal. Several parameter-efficient methods have been proposed in order to deal with reducing computational resources during training, such as: - Adapters: small neural network modules are inserted into each layer of a pertained model - Low-Rank Adaptation: training smaller low-rank matrices that are added to the existing weights - Prefix-tuning: adjusting the prefix embeddings without altering the model's weights -Sparse Fine-tuning: training only a subset of the model's parameters based on their relevance for a specific task The goal of the project is to conduct a comprehensive comparative study of the different approaches, and provide insights into the strength and drawbacks of such methods in different contexts.

Resources

Background

Url

Difficulty Level

Moderate

Ethical Approval

None

Number Of Students

1

Supervisor

Radu-Casian Mihailescu

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Bachelor of Science in Software Development for Business (GA)
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics
Bachelor of Science in Computer Science (Cyber Security)
Master of Science in Robotics with Industrial Application
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science