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NExT-GPT/NExT-GPT

The first end-to-end multimodal large language model (MM-LLM) capable of perceiving and generating content in arbitrary combinations 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: Provides a unified framework for multimodal understanding and generation.

Modular Design: Integrates pre-trained LLMs, multimodal encoders, and state-of-the-art diffusion models.

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

Flexible Output Generation: LLM generates 'modality signal' tokens to dictate specific multimodal content generation.

Detailed Introduction

NExT-GPT is a pioneering end-to-end multimodal large language model (MM-LLM) presented as an ICML 2024 oral paper. It distinguishes itself by its "any-to-any" capability, allowing it to perceive inputs and generate outputs in arbitrary combinations of text, image, video, and audio. Built upon existing pre-trained LLMs, multimodal encoders, and advanced diffusion models, NExT-GPT employs a three-stage architecture: multimodal encoding, LLM understanding and reasoning, and multimodal generation, all refined through extensive instruction tuning. This project represents a significant step towards truly unified multimodal AI.