一作ACL 2026Poster· Natural Language Processing
Towards Intrinsic Interpretability of Large Language Models: A Survey of Design Principles and Architectures
Yutong Gao · Qinglin Meng · Yuan Zhou · Liangming Pan
摘要
While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and safe deployment. Existing surveys in explainable AI largely focus on post-hoc explanation methods that interpret trained models through external a...