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 …

Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during
retrieval and, as a result, falls short in handling networked documents which are very …

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 …

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 …

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

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 …

Multimodal document understanding is a challenging task to process and comprehend large
amounts of textual and visual information. Recent advances in Large Language Models …

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 …

To process contexts with unlimited length using Large Language Models (LLMs), recent
studies explore hierarchically managing the long text. Only several text fragments are taken …