Fast-Slow Efficient Training for Multimodal Large Language Models via Visual Token Pruning

TL;DR

The paper introduces DualSpeed, a dual-mode training framework for multimodal large language models that combines fast token pruning with full sequence training to improve efficiency without sacrificing performance.

Contribution

It proposes a novel dual-mode training approach that integrates visual token pruning with full sequence training and self-distillation for efficient multimodal model training.

Findings

Accelerates LLaVA-1.5 training by 2.1×

Speeds up LLaVA-NeXT training by 4.0×

Retains over 99% of the original performance

Abstract

Multimodal Large Language Models (MLLMs) suffer from severe training inefficiency issue, which is associated with their massive model sizes and visual token numbers. Existing efforts in efficient training focus on reducing model sizes or trainable parameters. Inspired by the success of Visual Token Pruning (VTP) in improving inference efficiency, we are exploring another substantial research direction for efficient training by reducing visual tokens. However, applying VTP at the training stage results in a training-inference mismatch: pruning-trained models perform poorly when inferring on non-pruned full visual token sequences. To close this gap, we propose DualSpeed, a fast-slow framework for efficient training of MLLMs. The fast-mode is the primary mode, which incorporates existing VTP methods as plugins to reduce visual tokens, along with a mode isolator to isolate the model's behaviors. The slow-mode is the auxiliary mode, where the model is trained on full visual sequences to retain training-inference consistency. To boost its training, it further leverages self-distillation to learn from the sufficiently trained fast-mode. Together, DualSpeed can achieve both training efficiency and non-degraded performance. Experiments show DualSpeed accelerates the training of LLaVA-1.5 by 2.1$\times$ and LLaVA-NeXT by 4.0$\times$, retaining over 99% performance. Code: https://github.com/dingkun-zhang/DualSpeed