Google AI and the University of California have proposed the PixelLLM vision-language model to tackle challenges in localization and alignment faced by large language models. PixelLLM successfully addresses these challenges by establishing dense alignment between each output word of the language model and pixel positions. In visual tasks, PixelLLM demonstrates outstanding performance, including dense object descriptions, position-conditioned descriptions, and reference localization. This research represents a significant advancement in the field of large language models, aiming for more precise vision-language integration.