Author

C. K. Leung

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#artificial intelligence Preprint Sep 2026

Accuracy is Not Enough: A Divergence-Based Approach to Evaluate Fidelity Loss in Quantized LLMs

Deployment of Large Language Models (LLMs) on memory-constrained edge devices relies heavily on aggressive post-training quantization. However, evaluating these models is largely based on zero-shot task accuracy, which depends solely on argmax predictions and is insensitive to changes in the underlying predictive distr...

Shahzeb Qamar, L. Sparrenberg, Christian Bauckhage et al. · 1 citation

#artificial intelligence Dec 2024

Hyperedge Anomaly Detection with Hypergraph Neural Network

This work proposes an end-to-end hypergraph neural network-based model for identifying anomalous associations in a hypergraph that operates in an unsupervised manner without requiring any labeled data.

Md. Tanvir Alam, Md Mahmudur Rahman, Mohammad Fahim Arefin et al. · arXiv.org · 2 citations

Jul 2026

The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs

This work proposes Correctness Agreement, a decision-level metric that can measure the intersection of correct predictions between the base model and its quantized variant, and finds that the base and quantized variants usually have a shift in behavior even when accuracy and perplexity are preserved.

Baha Rababah, Shahzeb Qamar, Lorenz Sparrenberg et al. · arXiv.org · 0 citations