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cs.CL2024
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Weixin Liang, Lili Yu, Liang Luo +8
The development of large language models (LLMs) has expanded to multi-modal systems capable of processing text, images, and speech within a unified framework. Training these models…
cs.AI2024★ 4 cited
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts
Xi Victoria Lin, Akshat Shrivastava, Liang Luo +5
We introduce MoMa, a novel modality-aware mixture-of-experts (MoE) architecture designed for pre-training mixed-modal, early-fusion language models. MoMa processes images and text…