Revisiting the Reliability of Language Models in Instruction-Following 事件

Revisiting the Reliability of Language Models in Instruction-Following arXiv:2512.14754v3 Announce Type: replace-cross Abstract: Advanced LLMs have achieved near-ceiling instruction-following accuracy on benchmarks such as IFEval. However, these impressive scores do not necessarily translate to reliable services in real-world use, where users often vary their phrasing, contextual framing, and task formulations. In this paper, we study nuance-oriented reliability: whether models exhibit consiste