5 papers
Enhancing Transformer Representations of Symbolic ODE Expressions
Xiyue Fan, Adam Prugel-Bennett, Stuart E. Middleton
Existing approaches to solving differential equations, such as symbolic regression, physics informed neural networks, and neural operators, typically focus on numerical approximati…
LLM-based Visual Code Completion for Aerospace Geometric Design
Hau Kit Yong, Robert Marsh, Edmar A. Silva +2
Recent advances in both Large Language Models (LLMs) and Vision Language Models (VLMs) have seen a step change in their ability to perform visual code completion, but the aerospace…
Hybrid Adversarial Defence for Natural Language Understanding Tasks
Manar Abouzaid, Yang Wang, Chenghua Lin +1
Large Language Models (LLMs) are vulnerable both to hallucination and adversarial manipulation. Although these problems are closely related, existing defences typically address the…
Activation-Based Active Learning for In-Context Learning: Challenges and Insights
Yaseen M. Osman, Geoff V. Merrett, Stuart E. Middleton
Deep active learning has previously been explored for LLM in-context sample selection, but not with methods that utilise recent advances in understanding of transformer activations…
Adversarial Defence without Adversarial Defence: Enhancing Language Model Robustness via Instance-level Principal Component Removal
Yang Wang, Chenghao Xiao, Yizhi Li +3
Pre-trained language models (PLMs) have driven substantial progress in natural language processing but remain vulnerable to adversarial attacks, raising concerns about their robust…