Large language models (LLMs) excel at using textual reasoning to understand the context of a document and provide a logical ...

See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to ...

Characterization of intracellular synapse heterogeneity aides to understand the intricate computational logic of neuronal circuits. Despite recent advances in connectomics, the spatial patterns of ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

We propose a sampling-based method, called RSP-Hist, to construct approximate equi-width histograms and help data scientists explore the probability distribution of big data on Hadoop clusters. In RSP ...

Data-to-text Generation (D2T) aims to generate textual natural language statements that can fluently and precisely describe the structured data such as graphs, tables, and meaning representations (MRs ...

nlp ai text-analysis docx data-extraction contract-analysis legaltech docx2txt unstructured-data document-intelligence llm docx2md prompt-engineering llms generative-ai llm-framework llm-pipeline ...