12 citations · 14 across the 5 of their papers we have counts for
4 papers · 1 filter
Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation
Paul Darm, Cem Alpturk, Kenneth Ulrich +3
Automated optimisation is increasingly adopted in industrial processes, yet a trust gap persists between engineers who design these algorithms and operators who must act on their r…
Inference-Time Intervention in Large Language Models for Reliable Requirement Verification
Paul Darm, James Xie, Annalisa Riccardi
Steering the behavior of Large Language Models (LLMs) remains a challenge, particularly in engineering applications where precision and reliability are critical. While fine-tuning…
FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM
Grace Colverd, Paul Darm, Leonard Silverberg +1
Fast disaster impact reporting is crucial in planning humanitarian assistance. Large Language Models (LLMs) are well known for their ability to write coherent text and fulfill a va…
Knowledge Base Question Answering for Space Debris Queries
Paul Darm, Antonio Valerio Miceli-Barone, Shay B. Cohen +1
Space agencies execute complex satellite operations that need to be supported by the technical knowledge contained in their extensive information systems. Knowledge bases (KB) are…