The Abstraction Gap in Vision-Language Causal Reasoning 事件

The Abstraction Gap in Vision-Language Causal Reasoning arXiv:2605.28779v1 Announce Type: cross Abstract: Vision-language models (VLMs) generate fluent causal explanations, but current evaluations cannot distinguish linguistic plausibility from faithful causal reasoning. We introduce a dual-probe methodology that isolates these properties. The Text-Only Probe measures linguistic quality. The Chain-Text Probe requires models to first generate explicit causal chains. The Abstraction Gap (AG) metr