6 citations · 6 across the 4 of their papers we have counts for
4 papers
Faster, Cheaper, More Accurate: Specialised Knowledge Tracing Models Outperform LLMs
Prarthana Bhattacharyya, Joshua Mitton, Ralph Abboud +1
Predicting future student responses to questions is particularly valuable for educational learning platforms where it enables effective interventions. One of the key approaches to…
Misconception Diagnosis From Student-Tutor Dialogue: Generate, Retrieve, Rerank
Joshua Mitton, Prarthana Bhattacharyya, Digory Smith +3
Timely and accurate identification of student misconceptions is key to improving learning outcomes and pre-empting the compounding of student errors. However, this task is highly d…
Knowing When to Defer: Selective Prediction for Responsible Knowledge Tracing
Joshua Mitton, Prarthana Bhattacharyya, Ralph Abboud +1
Research on Knowledge Tracing (KT) models traditionally focuses on improving predictive accuracy. However, responsible real-world deployment requires models to know when to defer u…
BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in Biology
Odhran O'Donoghue, Aleksandar Shtedritski, John Ginger +4
The ability to automatically generate accurate protocols for scientific experiments would represent a major step towards the automation of science. Large Language Models (LLMs) hav…