Hierarchical Pre-Training of Vision Encoders with Large Language Models
The field of computer vision has experienced significant advancements through scalable vision encoders and multimodal pre-training frameworks. However, existing approaches often treat vision encoders and large language models (LLMs) as independent modules, limiting the integration of hierarchical visual features. In this work, we propose HIVE (Hierarchical Pre-Training of Vision Encoders), a novel framework that enhances vision-language alignment by introducing hierarchical cross-attention betwe
Record details
Published: 31 March 2026
Source: arXiv
Category: Research
Topics: Safety & alignment
Retrieved: 14 July 2026
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ethics.ai (31 March 2026), “Hierarchical Pre-Training of Vision Encoders with Large Language Models,” evidence record 6529, https://ethics.ai/record/6529 (originally published by arXiv).
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