1 citations · 1 across the 3 of their papers we have counts for
4 papers
Assessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs
Shasha Zhou, Mingyu Huang, Jack Cole +4
The recent proliferation of large language models (LLMs) holds the potential to revolutionize healthcare, with strong capabilities in diverse medical tasks. Yet, deploying LLMs in…
Don't throw the baby out with the bathwater: How and why deep learning for ARC
Jack Cole, Mohamed Osman
The Abstraction and Reasoning Corpus (ARC-AGI) presents a formidable challenge for AI systems. Despite the typically low performance on ARC, the deep learning paradigm remains the…
OmniGenBench: A Modular Platform for Reproducible Genomic Foundation Models Benchmarking
Heng Yang, Jack Cole, Yuan Li +3
The code of nature, embedded in DNA and RNA genomes since the origin of life, holds immense potential to impact both humans and ecosystems through genome modeling. Genomic Foundati…
OmniGenBench: Automating Large-scale in-silico Benchmarking for Genomic Foundation Models
Heng Yang, Jack Cole, Ke Li
The advancements in artificial intelligence in recent years, such as Large Language Models (LLMs), have fueled expectations for breakthroughs in genomic foundation models (GFMs). T…