3 papers
cs.CL2026
Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures
Yutong Gao, Qinglin Meng, Yuan Zhou +1
While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and safe deployment. Existing sur…
cs.AI2026
Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language Models
Danchun Chen, Qiyao Yan, Liangming Pan
Understanding how Large Language Models (LLMs) perform logical reasoning internally remains a fundamental challenge. While prior mechanistic studies focus on identifying taskspecif…
cs.AI2025
CausalEval: Towards Better Causal Reasoning in Language Models
Longxuan Yu, Delin Chen, Siheng Xiong +6
Causal reasoning (CR) is a crucial aspect of intelligence, essential for problem-solving, decision-making, and understanding the world. While language models (LMs) can generate rat…