Document Classification
207 papers with code • 19 benchmarks • 15 datasets
Document Classification is a procedure of assigning one or more labels to a document from a predetermined set of labels.
Benchmarks
These leaderboards are used to track progress in Document Classification
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Libraries
Use these libraries to find Document Classification models and implementationsDatasets
Cora
MPQA Opinion Corpus
IMDB-MULTI
SciDocs
HOC
Latest papers
Visually Guided Generative Text-Layout Pre-training for Document Intelligence
Prior study shows that pre-training techniques can boost the performance of visual document understanding (VDU), which typically requires models to gain abilities to perceive and reason both document texts and layouts (e. g., locations of texts and table-cells).
NextLevelBERT: Investigating Masked Language Modeling with Higher-Level Representations for Long Documents
aiintelligentsystems/next-level-bert
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While (large) language models have significantly improved over the last years, they still struggle to sensibly process long sequences found, e. g., in books, due to the quadratic scaling of the underlying attention mechanism.
Prompted Contextual Vectors for Spear-Phishing Detection
Spear-phishing attacks present a significant security challenge, with large language models (LLMs) escalating the threat by generating convincing emails and facilitating target reconnaissance.
ANLS* -- A Universal Document Processing Metric for Generative Large Language Models
However, evaluating GLLMs presents a challenge as the binary true or false evaluation used for discriminative models is not applicable to the predictions made by GLLMs.
GeoGalactica: A Scientific Large Language Model in Geoscience
To our best knowledge, it is the largest language model for the geoscience domain.
MELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRA
bruthyu/melo
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Large language models (LLMs) have shown great success in various Natural Language Processing (NLP) tasks, whist they still need updates after deployment to fix errors or keep pace with the changing knowledge in the world.
Summarization-based Data Augmentation for Document Classification
etsurin/summaug
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Despite the prevalence of pretrained language models in natural language understanding tasks, understanding lengthy text such as document is still challenging due to the data sparseness problem.
SUT: a new multi-purpose synthetic dataset for Farsi document image analysis
This paper introduces a new large-scale dataset for Farsi document images, named SUT, which aims to tackle the challenges associated with obtaining diverse and substantial ground-truth data for supervised models in document image analysis (DIA) tasks, such as document image classification, text detection and recognition, and information retrieval.
ContraDoc: Understanding Self-Contradictions in Documents with Large Language Models
In recent times, large language models (LLMs) have shown impressive performance on various document-level tasks such as document classification, summarization, and question-answering.
Optimal Transport for Measures with Noisy Tree Metric
It is known that such OT problem (i. e., tree-Wasserstein (TW)) admits a closed-form expression, but depends fundamentally on the underlying tree structure over supports of input measures.
