2 papers
cs.CL2026
When Quantization Preserves Accuracy but Not Evidence: Explanation-Aware Post-Training Quantization for Medical LLMs
Yeji Kim, Mi-Young Kim, Randy Goebel
Post-training quantization (PTQ) enables efficient deployment of large language models, and PTQ methods are usually optimized and evaluated with generic reconstruction, perplexity,…
cs.LG2026
Does Role Specialization Matter for Explanation Faithfulness in Mixture-of-Experts?
Yeji Kim, Housam Babiker, Mi-Young Kim +1
Mixture-of-Experts (MoE) architectures have recently been extended with role-based mechanisms for interpretability. This is typically done by assigning semantic roles to individual…