핵심 개념
DREAMLLM is a versatile learning framework that enables the comprehension and creation of multimodal content through synergistic modeling.
초록
The paper introduces DREAMLLM, a learning framework that focuses on achieving versatile Multimodal Large Language Models (MLLMs) empowered with synergy between multimodal comprehension and creation. The framework operates on two fundamental principles: generative modeling of language and image posteriors by direct sampling in the raw multimodal space, fostering the generation of raw, interleaved documents. DREAMLLM is capable of generating free-form interleaved content, showcasing superior performance as a zero-shot multimodal generalist.
ABSTRACT:
Introduces DREAMLLM, a learning framework for MLLMs.
Focuses on synergy between comprehension and creation.
Operates on generative modeling of language and image posteriors.
INTRODUCTION:
Multimodal Large Language Models (MLLMs) are crucial for machine intelligence.
DREAMLLM aims to enhance both comprehension and creation in multimodality.
DATA EXTRACTION:
"DREAMLLM is the first MLLM capable of generating free-form interleaved content."
"DREAMLLM achieves an 8.46 FID on MS-COCO."
통계
DREAMLLMは、初めて自由形式の交互コンテンツを生成できる最初のMLLMです。
DREAMLLMはMS-COCOで8.46のFIDを達成しました。