Beyond Surface Alignment: Grounding the Dynamics of Situational Understanding and Generative Control in LLMs

Paper recorded by Signals 4 on 2026-08-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CL · 自然语言处理 · first seen 2026-09-01

Abstract

The current alignment tuning paradigm for Large Language Models (LLMs) prioritizes surface-level behaviors -- fluency, safety, and tonal consistency. While effective for casual chat, this thesis argues that such surface alignment masks a lack of grounding, creating models that are stylistically confident but situationally brittle. We propose a framework of Grounded Alignment, analyzing how models

Read on arXiv →