Qiming Peng — accepted AI-conference papers

2026

Unleashing the Intrinsic Visual Representation Capability of Multimodal Large Language Models

Hengzhuang Li, Xinsong Zhang, Qiming Peng, Bin Luo, Han Hu, Dengyang Jiang +3

CVPR 2026

Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in multimodal tasks.Despite their impressive performance, MLLMs suffer from the modality imbalance issue, where visual information is often underutilized compared to textual representations in deeper layers, leading to

Cited by 0 Source ↗code ↗Scholar ↗

2022

ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document Understanding

Qiming Peng, Yinxu Pan, Wenjin Wang, Bin Luo, Zhenyu Zhang, Zhengjie Huang +9

EMNLP 2022finding

Recent years have witnessed the rise and success of pre-training techniques in visually-rich document understanding. However, most existing methods lack the systematic mining and utilization of layout-centered knowledge, leading to sub-optimal performances. In this paper, we propose ERNIE-Layout, a…

Cited by 86 Source ↗PDF ↗code ↗Scholar ↗