DocLLM: A layout-aware generative language model for multimodal document understanding
Enterprise documents such as forms, invoices, receipts, reports, contracts, and other similar
records, often carry rich semantics at the intersection of textual and spatial modalities. The …
records, often carry rich semantics at the intersection of textual and spatial modalities. The …
PDFTriage: question answering over long, structured documents
Large Language Models (LLMs) have issues with document question answering (QA) in
situations where the document is unable to fit in the small context length of an LLM. To …
situations where the document is unable to fit in the small context length of an LLM. To …
Instructdoc: A dataset for zero-shot generalization of visual document understanding with instructions
We study the problem of completing various visual document understanding (VDU) tasks,
eg, question answering and information extraction, on real-world documents through human …
eg, question answering and information extraction, on real-world documents through human …
Visual cot: Unleashing chain-of-thought reasoning in multi-modal language models
This paper presents Visual CoT, a novel pipeline that leverages the reasoning capabilities of
multi-modal large language models (MLLMs) by incorporating visual Chain-of-Thought …
multi-modal large language models (MLLMs) by incorporating visual Chain-of-Thought …
Privacy-aware document visual question answering
Document Visual Question Answering (DocVQA) is a fast growing branch of document
understanding. Despite the fact that documents contain sensitive or copyrighted information …
understanding. Despite the fact that documents contain sensitive or copyrighted information …
Bridging the Gap Between End-to-End and Two-Step Text Spotting
Modularity plays a crucial role in the development and maintenance of complex systems.
While end-to-end text spotting efficiently mitigates the issues of error accumulation and sub …
While end-to-end text spotting efficiently mitigates the issues of error accumulation and sub …
ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models
Recent advancements in AI have led to the development of large multimodal models (LMMs)
capable of processing complex tasks involving joint reasoning over text and visual content in …
capable of processing complex tasks involving joint reasoning over text and visual content in …
ICDAR 2023 competition on document understanding of everything (DUDE)
This paper presents the results of the ICDAR 2023 competition on Document UnderstanDing
of Everything. DUDE introduces a new dataset comprising 5 K visually-rich documents …
of Everything. DUDE introduces a new dataset comprising 5 K visually-rich documents …
Beyond Document Page Classification: Design, Datasets, and Challenges
J Van Landeghem, S Biswas… - Proceedings of the …, 2024 - openaccess.thecvf.com
This paper highlights the need to bring document classification benchmarking closer to real-
world applications, both in the nature of data tested (X: multi-channel, multi-paged, multi …
world applications, both in the nature of data tested (X: multi-channel, multi-paged, multi …
ANLS*--A Universal Document Processing Metric for Generative Large Language Models
D Peer, P Schöpf, V Nebendahl, A Rietzler… - arXiv preprint arXiv …, 2024 - arxiv.org
Traditionally, discriminative models have been the predominant choice for tasks like
document classification and information extraction. These models make predictions that fall …
document classification and information extraction. These models make predictions that fall …