Datasets are foundational to many breakthroughs in modern artificial intelligence. Many
recent achievements in the space of natural language processing (NLP) can be attributed to …

As scientific literature has grown exponentially, researchers often rely on paper triaging
strategies such as browsing abstracts before deciding to delve into a paper's full text …

For large language models (LLMs) to be effective in the financial domain--where each
decision can have a significant impact--it is necessary to investigate realistic tasks and data …

Large language models (LLMs) predominantly employ decoder-only transformer
architectures, necessitating the retention of keys/values information for historical tokens to …

In this report, we introduce DocXChain, a powerful open-source toolchain for document
parsing, which is designed and developed to automatically convert the rich information …

This work explores knowledge distillation (KD) for visually-rich document (VRD) applications
such as document layout analysis (DLA) and document image classification (DIC). While …

Document assistant chatbots are empowered with extensive capabilities by Large Language
Models (LLMs) and have exhibited significant advancements. However, these systems may …

Navigating the vast scientific literature often starts with browsing a paper's abstract.
However, when a reader seeks additional information, not present in the abstract, they face …

Parsing documents from pixels, such as pictures and scanned PDFs, into hierarchical
structures is extensively demanded in the daily routines of data storage, retrieval and …

The ability to understand and answer questions over documents can be useful in many
business and practical applications. However, documents often contain lengthy and diverse …