1 citations · 1 across the 6 of their papers we have counts for
6 papers
Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction
Haoqiu Yan, Yongxin Zhu, Kai Zheng +4
Large Language Model (LLM)-enhanced agents become increasingly prevalent in Human-AI communication, offering vast potential from entertainment to professional domains. However, cur…
HRVDA: High-Resolution Visual Document Assistant
Chaohu Liu, Kun Yin, Haoyu Cao +6
Leveraging vast training data, multimodal large language models (MLLMs) have demonstrated formidable general visual comprehension capabilities and achieved remarkable performance a…
Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration
Haoyu Cao, Changcun Bao, Chaohu Liu +6
We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including…
Turning a CLIP Model into a Scene Text Spotter
Wenwen Yu, Yuliang Liu, Xingkui Zhu +3
We exploit the potential of the large-scale Contrastive Language-Image Pretraining (CLIP) model to enhance scene text detection and spotting tasks, transforming it into a robust ba…
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
GMN: Generative Multi-modal Network for Practical Document Information Extraction
Haoyu Cao, Jiefeng Ma, Antai Guo +5
Document Information Extraction (DIE) has attracted increasing attention due to its various advanced applications in the real world. Although recent literature has already achieved…