Data Quality for LLMs: Building a Reliable Data Foundation

April 24, 2024 | 11:00 AM – 12:00 PM

Virtual

Add to Outlook Calendar

Register and join

Watch the recording

If you use large language models (LLMs) in your cancer research, register for this seminar to hear Elucidata’s Dr. Abhishek Jha discuss how data quality impacts LLM performance.

A reliable foundation that is well annotated and accessible to an LLM plays a major role in the value of its results.

You’ll see examples of how LLM-powered artificial intelligence (AI) agents query across three versions of the same gene expression corpus with differing results, including:

• unstructured data from the public repository Gene Expression Omnibus.
• structured data from the Crowd Extracted Expression of Differential Signatures project (tool developed by the Ma’ayan Lab at the Icahn School of Medicine at Mount Sinai).
• clean, linked, and harmonized data.

Dr. Jha will use these examples to discuss how the different quality in these data sources impacts LLM performance.