9 citations · 18 across the 6 of their papers we have counts for
6 papers
Unlimited OCR Works
Youyang Yin, Huanhuan Liu, YY +14
Recently, end-to-end OCR models, exemplified by DeepSeek OCR, have once again thrust OCR into the spotlight. A widely held view is that employing a large language model (LLM) as th…
General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
Haoran Wei, Chenglong Liu, Jinyue Chen +9
Traditional OCR systems (OCR-1.0) are increasingly unable to meet people's usage due to the growing demand for intelligent processing of man-made optical characters. In this paper,…
Focus Anywhere for Fine-grained Multi-page Document Understanding
Chenglong Liu, Haoran Wei, Jinyue Chen +7
Modern LVLMs still struggle to achieve fine-grained document understanding, such as OCR/translation/caption for regions of interest to the user, tasks that require the context of t…
OneChart: Purify the Chart Structural Extraction via One Auxiliary Token
Jinyue Chen, Lingyu Kong, Haoran Wei +6
Chart parsing poses a significant challenge due to the diversity of styles, values, texts, and so forth. Even advanced large vision-language models (LVLMs) with billions of paramet…
Small Language Model Meets with Reinforced Vision Vocabulary
Haoran Wei, Lingyu Kong, Jinyue Chen +6
Playing Large Vision Language Models (LVLMs) in 2023 is trendy among the AI community. However, the relatively large number of parameters (more than 7B) of popular LVLMs makes it d…
Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models
Haoran Wei, Lingyu Kong, Jinyue Chen +6
Modern Large Vision-Language Models (LVLMs) enjoy the same vision vocabulary -- CLIP, which can cover most common vision tasks. However, for some special vision task that needs den…