Lisa Alazraki

Hi! I am a third year PhD student in the NLP Group at Imperial College London, supervised by Marek Rei. I am broadly interested in the relationship between reasoning and language. I also have an interest in model robustness to input perturbations and adversarial attacks.

Currently, I am affiliated with the Alan Turing Institute as a recipient of the Enrichment Scheme Placement Award. Previously, I was a Research Intern at Cohere (2024) and Google (2022, 2023).

News

22 May 2025
New preprint! Reverse Engineering Human Preferences with Reinforcement Learning

29 Apr 2024
Going to NAACL to present Meta-Reasoning Improves Tool Use in Large Language Models ✈️

13 Feb 2025
Our new preprint No Need for Explanations: LLMs can implicitly learn from mistakes in-context is available on ArXiv!

6 Dec 2024
Meta-Reasoning Improves Tool Use in Large Language Models won first prize at the Imperial Computing Conference 🎉

Research

	Reverse Engineering Human Preferences with Reinforcement Learning Lisa Alazraki, Tan Yi-Chern, Jon Ander Campos, Maximilian Mozes, Marek Rei, Max Bartolo arXiv, 2025 paper
	No Need for Explanations: LLMs can implicitly learn from mistakes in-context Lisa Alazraki, Maximilian Mozes, Jon Ander Campos, Tan Yi-Chern, Marek Rei, Max Bartolo arXiv, 2025 paper / code
	How to Improve the Robustness of Closed-Source Models on NLI Joe Stacey, Lisa Alazraki, Aran Ubhi, Beyza Ermis, Aaron Mueller, Marek Rei arXiv, 2025 paper / code
	Enhancing LLM Robustness to Perturbed Instructions: An Empirical Study Aryan Agrawal, Lisa Alazraki*, Shahin Honarvar, Marek Rei (Equal contribution) BuildingTrust @ICLR, 2025 paper / code
	How Can Representation Dimension Dominate Structurally Pruned LLMs? Mingxue Xu, Lisa Alazraki, Danilo P. Mandic SLLM @ICLR, 2025 paper
	Meta-Reasoning Improves Tool Use in Large Language Models Lisa Alazraki, Marek Rei NAACL Findings, 2025 paper / code
	Meta-Reasoning Improves Tool Use in Large Language Models Lisa Alazraki, Lluis Castrejon, Mostafa Dehghani, Fantine Huot, Jasper Uijlings, Thomas Mensink PMLR Proceedings on ICBINB @NeurIPS, 2025 paper

Teaching

I am a Teaching Assistant for 70050 Intro to Machine Learning, 70016 Natural Language Processing, 70010 Deep Learning and 40008 Graphs and Algorithms.

Supervision

2025
Kevin Zhou 'Optimal Data Mixing Strategies at Different Token Budgets for Language Model Training', MSc dissertation, co-supervised with Marek Rei (Imperial College London) and Kris Cao (Cohere).

2024
Aryan Agrawal 'Improving the Robustness of LLMs to Prompt Perturbations', MSc dissertation, co-supervised with Marek Rei (Imperial College London), Thomas Mensink (Google Research) and Shahin Honarvar (Imperial College London).

2023
Ziheng Zhang 'Knowledge-Enhanced Supportive Memory for Chatbots', MEng dissertation, co-supervised with the Algorithmic Human Development group (Imperal College London) and Zissis Poulos (University of Toronto).

2022
Alicia Law 'A Multilingual Chatbot for Self-Attachment Therapy', MSc dissertation (Distinguished Dissertation award), co-supervised with the Algorithmic Human Development group (Imperial College London).

Service

Conference reviewing: ACL 2025, COLING 2025, COLM 2025, EMNLP 2025, NAACL 2025
Workshop reviewing: ACL-SRW 2025, BuildingTrust @ICLR 2025, ICBINB @ICLR 2025, MARW @AAAI 2025

Forked from Jon Barron's website.