31 citations · 31 across the 5 of their papers we have counts for
6 papers
Evaluating Inquiry Learning in LLM-Based Agents: Hypothesizing, Reasoning, and Exploration
Marta Knežević, Seyed Parsa Neshaei, Jibril Frej +2
Scientific inquiry involves iterative cycles of exploration, hypothesis generation, and reasoning over observations to uncover relationships in complex systems. Large language mode…
SCATR: Simple Calibrated Test-Time Ranking
Divya Shyamal, Marta Knežević, Lan Tran +3
Test-time scaling (TTS) improves large language models (LLMs) by allocating additional compute at inference time. In practice, TTS is often achieved through parallel scaling: gener…
Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student Attacks
Jin Zhao, Marta Knežević, Tanja Käser
Large Language Models (LLMs) are increasingly used in education, yet their default helpfulness often conflicts with pedagogical principles. Prior work evaluates pedagogical quality…
REFINE: Real-world Exploration of Interactive Feedback and Student Behaviour
Fares Fawzi, Seyed Parsa Neshaei, Marta Knezevic +2
Formative feedback is central to effective learning, yet providing timely, individualised feedback at scale remains a persistent challenge. While recent work has explored the use o…
Graph Reasoning for Explainable Cold Start Recommendation
Jibril Frej, Marta Knezevic, Tanja Kaser
The cold start problem, where new users or items have no interaction history, remains a critical challenge in recommender systems (RS). A common solution involves using Knowledge G…
Finding Paths for Explainable MOOC Recommendation: A Learner Perspective
Jibril Frej, Neel Shah, Marta Knežević +2
The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networ…