4 papers
ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images
Mathieu Sibue, Andres Muñoz Garza, Samuel Mensah +4
Enterprise documents, such as forms and reports, embed critical information for downstream applications like data archiving, automated workflows, and analytics. Although generalist…
LLM Agents for Automated Dependency Upgrades
Vali Tawosi, Salwa Alamir, Xiaomo Liu +1
As a codebase expands over time, its library dependencies can become outdated and require updates to maintain innovation and security. However, updating a library can introduce bre…
Meta-RAG on Large Codebases Using Code Summarization
Vali Tawosi, Salwa Alamir, Xiaomo Liu +1
Large Language Model (LLM) systems have been at the forefront of applied Artificial Intelligence (AI) research in a multitude of domains. One such domain is software development, w…
"What is the value of {templates}?" Rethinking Document Information Extraction Datasets for LLMs
Ran Zmigrod, Pranav Shetty, Mathieu Sibue +4
The rise of large language models (LLMs) for visually rich document understanding (VRDU) has kindled a need for prompt-response, document-based datasets. As annotating new datasets…