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cs.SE2026
CONQuER: Hardware-Aware Mixed-Precision Quantisation with Online-Calibrated Surrogates
Aidan Dakhama, Ajitha Rajan
Deploying deep neural networks on resource-constrained hardware relies on mixed-precision quantisation (MPQ). current deployment toolchains severely fragment this process. Quantisa…
cs.CV2026
Radiologist-Guided Causal Concept Bottleneck Models for Chest X-Ray Interpretation
Amy Rafferty, Rishi Ramaesh, Ajitha Rajan
Concept Bottleneck Models (CBMs) in medical imaging aim to improve model interpretability by predicting intermediate clinical concepts before final diagnoses. However, most existin…
cs.CV2026
Clinically Aware Synthetic Image Generation for Concept Coverage in Chest X-ray Models
Amy Rafferty, Rishi Ramaesh, Ajitha Rajan
Deep learning models for chest X-ray diagnosis are constrained by limited coverage of clinically meaningful concept combinations in publicly available training datasets. While synt…