Document parsing unveiled: Techniques, challenges, and prospects for structured information extraction
Document parsing is essential for converting unstructured and semi-structured documents-
such as contracts, academic papers, and invoices-into structured, machine-readable data …
such as contracts, academic papers, and invoices-into structured, machine-readable data …
Tabpedia: Towards comprehensive visual table understanding with concept synergy
Tables contain factual and quantitative data accompanied by various structures and
contents that pose challenges for machine comprehension. Previous methods generally …
contents that pose challenges for machine comprehension. Previous methods generally …
TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Text-centric visual question answering (VQA) has made great strides with the development
of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of …
of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of …
Mindbench: A comprehensive benchmark for mind map structure recognition and analysis
Multimodal Large Language Models (MLLM) have made significant progress in the field of
document analysis. Despite this, existing benchmarks typically focus only on extracting text …
document analysis. Despite this, existing benchmarks typically focus only on extracting text …
Doclayllm: An efficient and effective multi-modal extension of large language models for text-rich document understanding
Text-rich document understanding (TDU) refers to analyzing and comprehending
documents containing substantial textual content. With the rapid evolution of large language …
documents containing substantial textual content. With the rapid evolution of large language …
VL-Reader: Vision and Language Reconstructor is an Effective Scene Text Recognizer
Text recognition is an inherent integration of vision and language, encompassing the visual
texture in stroke patterns and the semantic context among the character sequences …
texture in stroke patterns and the semantic context among the character sequences …
InstructOCR: Instruction Boosting Scene Text Spotting
In the field of scene text spotting, previous OCR methods primarily relied on image encoders
and pre-trained text information, but they often overlooked the advantages of incorporating …
and pre-trained text information, but they often overlooked the advantages of incorporating …
DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness
Document Visual Question Answering (VQA) requires models to interpret textual information
within complex visual layouts and comprehend spatial relationships to answer questions …
within complex visual layouts and comprehend spatial relationships to answer questions …
Efficient title text detection using multi-loss
Abstract YouTube's “Video Chapter” feature segments videos into different sections, marked
by timestamps on the slider, enhancing user navigation. Given the vast volume of video …
by timestamps on the slider, enhancing user navigation. Given the vast volume of video …
Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner
Pre-trained foundation models have recently significantly progressed in structured table
understanding and reasoning. However, despite advancements in areas such as table …
understanding and reasoning. However, despite advancements in areas such as table …