This paper defines the "Plausibility Trap," a phenomenon where individuals over-rely on expensive probabilistic Large Language Models (LLMs) for simple deterministic tasks, leading to significant resource waste and risks like algorithmic sycophancy. It introduces a framework for proper tool selection and advocates for a curriculum shift in digital literacy.

AdaptVision introduces an efficient VLM paradigm that autonomously determines the minimum number of visual tokens required for each sample by employing a coarse-to-fine visual acquisition strategy, leading to superior performance with significantly reduced computational overhead.