12 papers
Estimating Learners' Skill Acquisition Without Temporal Information
Ryosuke Nagai, Kyohei Atarashi, Koh Takeuchi +2
Recent research in educational data mining, especially knowledge tracing, has focused on predicting learners' future knowledge states to support adaptive instruction. However, in m…
Long-Term Outlier Prediction Through Outlier Score Modeling
Yuma Aoki, Joon Park, Koh Takeuchi +6
This study addresses an important gap in time series outlier detection by proposing a novel problem setting: long-term outlier prediction. Conventional methods primarily focus on i…
Evaluating Cross-Modal Reasoning Ability and Problem Characteristics with Multimodal Item Response Theory
Shunki Uebayashi, Kento Masui, Kyohei Atarashi +5
Multimodal Large Language Models (MLLMs) have recently emerged as general architectures capable of reasoning over diverse modalities. Benchmarks for MLLMs should measure their abil…
Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
Clémence Réda, Tomas Rigaux, Hiba Bederina +3
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also mi…
Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems
Lijia Liu, Takumi Kondo, Kyohei Atarashi +4
This paper investigates defenses for LLM-based evaluation systems against prompt injection. We formalize a class of threats called blind attacks, where a candidate answer is crafte…
Robust Anomaly Detection Under Normality Distribution Shift in Dynamic Graphs
Xiaoyang Xu, Xiaofeng Lin, Koh Takeuchi +2
Anomaly detection in dynamic graphs is a critical task with broad real-world applications, including social networks, e-commerce, and cybersecurity. Most existing methods assume th…