6 papers
How Robust Are Large Language Models for Clinical Numeracy? An Empirical Study on Numerical Reasoning Abilities in Clinical Contexts
Minh-Vuong Nguyen, Fatemeh Shiri, Zhuang Li +1
Large Language Models (LLMs) are increasingly being explored for clinical question answering and decision support, yet safe deployment critically requires reliable handling of pati…
Simultaneous Machine Translation with Large Language Models
Minghan Wang, Jinming Zhao, Thuy-Trang Vu +3
Real-world simultaneous machine translation (SimulMT) systems face more challenges than just the quality-latency trade-off. They also need to address issues related to robustness w…
Bayesian Network Fusion of Large Language Models for Sentiment Analysis
Rasoul Amirzadeh, Dhananjay Thiruvady, Fatemeh Shiri
Large language models (LLMs) continue to advance, with an increasing number of domain-specific variants tailored for specialised tasks. However, these models often lack transparenc…
An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
Fatemeh Shiri, Xiao-Yu Guo, Mona Golestan Far +3
Large Multimodal Models (LMMs) have achieved strong performance across a range of vision and language tasks. However, their spatial reasoning capabilities are under-investigated. I…
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs
Minh-Vuong Nguyen, Linhao Luo, Fatemeh Shiri +4
Large language models (LLMs) demonstrate strong reasoning abilities when prompted to generate chain-of-thought (CoT) explanations alongside answers. However, previous research on e…
Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs
Fatemeh Shiri, Van Nguyen, Farhad Moghimifar +3
Large Language Models (LLMs) demonstrate significant capabilities in processing natural language data, promising efficient knowledge extraction from diverse textual sources to enha…