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cs.CL2026
More Than Seeing: Vision as Scalable Anchors in Native Multimodal Pre-Training
Haoyuan Wu, Aoqi Wu, Jiani Hu +1
Native multimodal pre-training trains a single model from scratch on text and multimodal data, enabling it to understand both language and visual inputs. However, how visual signal…
cs.CL2026
Scaling Native Multimodal Pre-Training From Scratch
Haoyuan Wu, Aoqi Wu, Hai Wang +3
Although large language models (LLMs) exhibit remarkable reasoning capabilities, their reliance on text-only pre-training restricts the perception of the multimodal physical world.…
cs.CL2026
Pretraining A Large Language Model using Distributed GPUs: A Memory-Efficient Decentralized Paradigm
Jinrui Zhang, Chaodong Xiao, Aoqi Wu +2
Pretraining large language models (LLMs) typically requires centralized clusters with thousands of high-memory GPUs (e.g., H100/A100). Recent decentralized training methods reduce…