The reliability of LLM outputs has direct implications downstream robotics tasks.

In this work, we present a dual-stage low-bit post-training quantization (PTQ) method for image super-resolution, namely 2DQuant, which achieves efficient and accurate SR under low-bit quantization.

Different distribution shifts require different algorithmic and operational interventions. Methodological research must be grounded by the specific shifts they address.