5 papers
Dynamic Bidirectional Pattern Memory: A Production-Scale Empirical Characterisation of Inference-Time Gating in Clinical NLP
Ali H. Lazem, William Teahan
We study inference-time pattern-memory gating in a production-scale clinical natural language processing (NLP) pipeline. The pipeline pairs a generator (Llama-3.3 70B) proposing ex…
How much of an LLM-generated clinical corpus is actually new? A production-scale measurement of content redundancy for provenance classification
Ali H. Lazem, William J. Teahan
Clinical machine learning increasingly relies on training corpora generated by large language models (LLMs) rather than annotated by clinicians, and such corpora are described and…
Task-Specific Activation Functions for Neuroevolution using Grammatical Evolution
Benjamin David Winter, William John Teahan
Activation functions play a critical role in the performance and behaviour of neural networks, significantly impacting their ability to learn and generalise. Traditional activation…
Ecological Neural Architecture Search
Benjamin David Winter, William J. Teahan
When employing an evolutionary algorithm to optimize a neural networks architecture, developers face the added challenge of tuning the evolutionary algorithm's own hyperparameters…
Evaluating a Novel Neuroevolution and Neural Architecture Search System
Benjamin David Winter, William John Teahan
The choice of neural network features can have a large impact on both the accuracy and speed of the network. Despite the current industry shift towards large transformer models, sp…