collaborators

7 papers

cs.CV2026

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

Gengluo Li, Xingyu Wan, Shangpin Peng +20

We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, information extraction, text-image tr…

cs.CV2026

ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formats

Shangpin Peng, Gengluo Li, Xingyu Wan +10

Charts are a primary medium for conveying quantitative and relational information, yet systematically evaluating chart parsing models remains difficult. Existing benchmarks focus o…

cs.CV2026

StrucTab: A Structured Optimization Framework for Table Parsing

Gengluo Li, Shangpin Peng, Chengquan Zhang +10

Table parsing aims to convert table images into structured, machine-readable representations, a task requiring the joint perception of complex spatial layouts and textual content.…

cs.CV2026

Chronicles-OCR: A Cross-Temporal Perception Benchmark for the Evolutionary Trajectory of Chinese Characters

Gengluo Li, Shangpin Peng, Xingyu Wan +16

Vision Large Language Models (VLLMs) have achieved remarkable success in modern text-rich visual understanding. However, their perceptual robustness in the face of the continuous m…

cs.CV2026

Towards Real-World Document Parsing via Realistic Scene Synthesis and Document-Aware Training

Gengluo Li, Pengyuan Lyu, Chengquan Zhang +7

Document parsing has recently advanced with multimodal large language models (MLLMs) that directly map document images to structured outputs. Traditional cascaded pipelines depend…

cs.CV2026

MMTIT-Bench: A Multilingual and Multi-Scenario Benchmark with Cognition-Perception-Reasoning Guided Text-Image Machine Translation

Gengluo Li, Chengquan Zhang, Yupu Liang +9

End-to-end text-image machine translation (TIMT), which directly translates textual content in images across languages, is crucial for real-world multilingual scene understanding.…