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NExT-GPT/NExT-GPT

The first end-to-end multimodal large language model (MM-LLM) that perceives input and generates output in arbitrary combinations (any-to-any) of text, image, video, and audio.

Core Features

Any-to-Any Multimodal Capability: Processes and generates content across text, image, video, and audio in arbitrary combinations.

End-to-End Architecture: Integrates multimodal encoding, LLM understanding/reasoning, and multimodal generation stages.

Leverages Pre-trained Models: Built upon existing LLMs, multimodal encoders, and state-of-the-art diffusion models.

Instruction Tuning: Enhanced performance through comprehensive end-to-end instruction tuning.

Modular Design: Clear separation of encoding, reasoning, and generation components for flexibility.

Detailed Introduction

NExT-GPT is a pioneering end-to-end multimodal large language model (MM-LLM) capable of processing and generating content in any combination of text, image, video, and audio. It addresses the critical challenge of unified multimodal understanding and generation by integrating established multimodal encoders, a powerful LLM for reasoning, and advanced diffusion models for content creation. This project, an ICML 2024 oral paper, provides the code, data, and model weights, enabling researchers and developers to explore and build upon its innovative any-to-any multimodal capabilities, pushing the boundaries of generative AI.