SEReDeEP replaces ReDeEP's lexical scores with semantic entropy probe scores, but its claimed 3-10% accuracy gains are contradicted by its own tables and its probes are trained on the evaluation datasets.
How to remove or control confounds in predictive models, with applications to brain biomarkers.GigaScience, 11:giac014, 2022
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
SEReDeEP: Hallucination Detection in Retrieval-Augmented Models via Semantic Entropy and Context-Parameter Fusion
SEReDeEP replaces ReDeEP's lexical scores with semantic entropy probe scores, but its claimed 3-10% accuracy gains are contradicted by its own tables and its probes are trained on the evaluation datasets.