20 citations · 21 across the 10 of their papers we have counts for
10 papers
Inferring Affective Consciousness in an Artificial Agent: A Case Study
Mark Solms, St John Grimbly, Bruce Bassett +7
Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attraction to pleasure-producing sub…
Artificial Intelligence Can Match Domain Experts in Evidence Extraction and Critical Appraisal of Microbial Oncogenesis Research Publications
Kaela Kokkas, Hairong Wang, Richard Klein +11
Confirmed oncogenic microbes contribute significantly to cancer burden. Identifying novel microbial oncogenicity could yield strategies that will reduce disease burdens. However, r…
Interoceptive Attention as Dynamic Homeostatic Prioritization in a Foraging Agent
St John Grimbly, Nicolas Kuske, Evert A. Boonstra +7
Biological systems must regulate competing needs under limited perceptual bandwidth, where sharpening one estimate costs the capacity to sharpen the others. Any fixed-budget system…
Evaluating Multimodal LLMs for Inpatient Diagnosis: Real-World Performance, Safety, and Cost Across Ten Frontier Models
Bruce A. Bassett, Amy Rouillard, Sitwala Mundia +8
Background: Large language models (LLMs) are increasingly proposed for diagnostic support, but few evaluations use real-world multimodal inpatient data, particularly in low and mid…
From Handwriting to Structured Data: Benchmarking AI Digitisation of Handwritten Forms
Nicholas Pather, Joshua Fouché, Sitwala Mundia +5
Manual digitisation of structured handwritten documents is slow and costly. We benchmark 17 leading frontier multi-modal large language models and open-source models against a very…
Can LLMs Accurately Score Medical Diagnoses and Clinical Reasoning?
Amy Rouillard, Sitwala Mundia, Linda Camara +8
Evaluating medical AI systems using expert clinician panels is costly and slow, motivating the use of large language models (LLMs) as alternative adjudicators. Here, we evaluate an…
Calibrating Beyond English: Language Diversity for Better Quantized Multilingual LLM
Everlyn Asiko Chimoto, Mostafa Elhoushi, Bruce A. Bassett
Quantization is an effective technique for reducing the storage footprint and computational costs of Large Language Models (LLMs), but it often results in performance degradation.…
Small Language Models Can Use Nuanced Reasoning For Health Science Research Classification: A Microbial-Oncogenesis Case Study
Muhammed Muaaz Dawood, Mohammad Zaid Moonsamy, Kaela Kokkas +5
Artificially intelligent (AI) co-scientists must be able to sift through research literature cost-efficiently while applying nuanced scientific reasoning. We evaluate Small Languag…
Critical Learning Periods: Leveraging Early Training Dynamics for Efficient Data Pruning
Everlyn Asiko Chimoto, Jay Gala, Orevaoghene Ahia +3
Neural Machine Translation models are extremely data and compute-hungry. However, not all data points contribute equally to model training and generalization. Data pruning to remov…
A new twist to preheating
S. Tsujikawa, B. A. Bassett
Metric perturbations typically strengthen field resonances during preheating. In contrast we present a model in which the super-Hubble field resonances are completely {\em suppress…