Research
The Impact of Visual Input on ARC Challenges
Status: In Progress
I'm interested in how model responses to ARC reasoning questions (grid-based logic puzzles) change when models are given text-only, vision-only and vision-language inputs.
Probing Negation Understanding in Vision-Language Models With Object Attention
Status: Submitted to ACL Rolling Review
I'm investigating how vision-language models like LLaVA handle negation, by comparing how their visual attention shifts when processing positive vs. negated versions of the same sentence and how this compares to human patterns.
Semantic Similarity in Radiology Reports via LLMs and NER
Status: Paper Accepted at AI Bio Workshop at ECAI 2025
We explore how large language models can help evaluate junior radiologists' reports by identifying meaningful differences from senior-edited versions through interpretable similarity scores.
Evaluating Compositional Generalisation in VLMs and Diffusion Models
Status: Paper accepted at *SEM (co-located with EMNLP 2025)
This work explores whether diffusion models can better handle compositional generalisation than models like CLIP, especially for understanding attributes and spatial relationships in images.