about me

Hi, I'm Nick. I'm currently on the job market for AI/ML Science positions!

I hold a Ph.D. from the University of Edinburgh and the Institute for Language, Cognition, and Computation. I also did my B.Sc. in Computer Science at Brown University.

My research spans several areas and methodologies in NLP. I have significant experient in natural language inference (NLI), especially to do with tasks like question answering, and data in the form of structured knowledge (Knowledge Graphs, Entailment Graphs) and unstructured, open-domain text in natural language. I also research Language Model capabilities in textual understanding, and do systematic analyses of their factual hallucination, and strategize mitigations.

Recent News:
04 Nov '23 Our paper, Smoothing Entailment Graphs with Language Models, won the "Best Paper" award at AACL 2023.
06 Oct '23 Our paper, Sources of Hallucination by Large Language Models on Inference Tasks, was accepted to EMNLP Findings.
06 Oct '23 I defended my Ph.D. thesis, Inference of Natural Language Predicates in the Open Domain.
selected publications

Nick McKenna*, Tianyi Li*, Liang Cheng, Mohammad Javad Hosseini, Mark Johnson, and Mark Steedman. Sources of Hallucination by Large Language Models on Inference Tasks. Findings of EMNLP, 2023. Preprint Link.

Nick McKenna, Tianyi Li, Mark Johnson, and Mark Steedman. Smoothing Entailment Graphs with Language Models. AACL, 2023. *Best Paper Award!* Preprint Link.

Nick McKenna, Liane Guillou, Mohammad Javad Hosseini, Sander Bijl de Vroe, Mark Johnson, and Mark Steedman. Multivalent Entailment Graphs for Question Answering. EMNLP, 2021. Paper Link.

For a full list of publications, refer to my CV.

contact

Reach me by email or find me on X/Twitter and LinkedIn.

© 2023 Nick McKenna