Andrew Parry

Email: a.parry.1@research.gla.ac.uk

Website: parry-parry.github.io

Office:

Room 502, Level 5

Sir Alwyn Williams Building

School of Computing Science

Glasgow, G12 8QQ

ORCID iDhttps://orcid.org/0000-0001-5446-8328

Research title: Modelling Uncertainties in Neural Networks for Improved Defence against Adversarial Attacks

Research Summary

I obtained my BSc in Computing Science from the University of Glasgow in 2022. After a research placement I joined the IR group at Glasgow working on search. I have made contributions to the PyTerrier framework maintained at Glasgow which can be accessed from my website.

Main Research Interests

  • Neural Ranking Models
  • Adversarial Attacks in Search
  • Efficient Neural Training

My Research

I am interested in how the overparameterized language models that underpin neural search often display behaviour which diverges from a user's notion of relevance. I am working to expose these weaknesses whilst improving efficiency to make neural search a more viable option in industry.

Publications

List by: Type | Date

Jump to: 2024 | 2023
Number of items: 5.

2024

Sinhababu, N., Parry, A., Ganguly, D. , Samanta, D. and Mitra, P. (2024) Few-shot Pairwise Ranking Prompting: An Effective Non-Parametric Retrieval Model. In: 2024 Conference on Empirical Methods in Natural Language Processing, Miami, Florida, USA, 12–16 November 2024, (Accepted for Publication)

Parry, A., MacAvaney, S. and Ganguly, D. (2024) Top-Down Partitioning for Efficient List-Wise Ranking. ReNeuIR'24, Washington, DC, USA, 18 July 2024. (Accepted for Publication)

Parry, A., MacAvaney, S. and Ganguly, D. (2024) Exploiting Positional Bias for Query-Agnostic Generative Content in Search. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, 11-16 August 2024, (Accepted for Publication)

Parry, A., Ganguly, D. and Chandra, M. (2024) In-Context Learning or: How I Learned to Stop Worrying and Love Applied Information Retrieval. In: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), Washington D.C., USA, 14-18 Jul 2024, (Accepted for Publication)

2023

Parry, A., Fröbe, M., MacAvaney, S. , Potthast, M. and Hagen, M. (2023) Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models. In: 46th European Conference on Information Retrieval (ECIR2024), Glasgow, Scotland, 24-28 March 2024, (Accepted for Publication)

This list was generated on Wed Apr 2 03:18:10 2025 BST.
Jump to: Conference or Workshop Item | Conference Proceedings
Number of items: 5.

Conference or Workshop Item

Parry, A., MacAvaney, S. and Ganguly, D. (2024) Top-Down Partitioning for Efficient List-Wise Ranking. ReNeuIR'24, Washington, DC, USA, 18 July 2024. (Accepted for Publication)

Conference Proceedings

Sinhababu, N., Parry, A., Ganguly, D. , Samanta, D. and Mitra, P. (2024) Few-shot Pairwise Ranking Prompting: An Effective Non-Parametric Retrieval Model. In: 2024 Conference on Empirical Methods in Natural Language Processing, Miami, Florida, USA, 12–16 November 2024, (Accepted for Publication)

Parry, A., MacAvaney, S. and Ganguly, D. (2024) Exploiting Positional Bias for Query-Agnostic Generative Content in Search. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, 11-16 August 2024, (Accepted for Publication)

Parry, A., Ganguly, D. and Chandra, M. (2024) In-Context Learning or: How I Learned to Stop Worrying and Love Applied Information Retrieval. In: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), Washington D.C., USA, 14-18 Jul 2024, (Accepted for Publication)

Parry, A., Fröbe, M., MacAvaney, S. , Potthast, M. and Hagen, M. (2023) Analyzing Adversarial Attacks on Sequence-to-Sequence Relevance Models. In: 46th European Conference on Information Retrieval (ECIR2024), Glasgow, Scotland, 24-28 March 2024, (Accepted for Publication)

This list was generated on Wed Apr 2 03:18:10 2025 BST.

Supervisors


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