PLKT models student knowledge with Beta probabilistic embeddings and performs explicit logical reasoning over historical interactions to deliver both accurate predictions and interpretable explanations in knowledge tracing.
Cikt: A collaborative and iterative knowledge trac- ing framework with large language models.arXiv preprint arXiv:2505.17705
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.AI 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
BuddyBench introduces a multi-task benchmark linking drill trajectories, clinical scores, self-reports, and RCT endpoints across 275 children in two cohorts for knowledge tracing, recommendation, prediction, and causal inference while preserving privacy.
citing papers explorer
-
Explainable Knowledge Tracing via Probabilistic Embeddings and Pattern-based Reasoning
PLKT models student knowledge with Beta probabilistic embeddings and performs explicit logical reasoning over historical interactions to deliver both accurate predictions and interpretable explanations in knowledge tracing.
-
BuddyBench: A Privacy-Constrained Multi-Task Benchmark for Pediatric Social-Communication Personalization
BuddyBench introduces a multi-task benchmark linking drill trajectories, clinical scores, self-reports, and RCT endpoints across 275 children in two cohorts for knowledge tracing, recommendation, prediction, and causal inference while preserving privacy.