Lisa Schut

According to our database, Lisa Schut authored at least 13 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Do Multilingual LLMs Think In English?

Lisa Schut, Yarin Gal, Sebastian Farquhar

CoRR, February, 2025

Explaining Explainability: Recommendations for Effective Use of Concept Activation Vectors.

Angus Nicolson, Lisa Schut, J. Alison Noble, Yarin Gal

Trans. Mach. Learn. Res., 2025

Hindsight Merging: Diverse Data Generation with Language Models.

Veniamin Veselovsky, Benedikt Stroebl, Gianluca M. Bencomo, Dilip Arumugam, Lisa Schut, Arvind Narayanan, Thomas L. Griffiths

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

2024

Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs.

Jannik Kossen, Jiatong Han, Muhammed Razzak, Lisa Schut, Shreshth A. Malik, Yarin Gal

CoRR, 2024

Explaining Explainability: Understanding Concept Activation Vectors.

Angus Nicolson, Lisa Schut, J. Alison Noble, Yarin Gal

CoRR, 2024

2023

Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero.

Lisa Schut, Nenad Tomasev, Tom McGrath, Demis Hassabis, Ulrich Paquet, Been Kim

CoRR, 2023

Diversifying AI: Towards Creative Chess with AlphaZero.

Tom Zahavy, Vivek Veeriah, Shaobo Hou, Kevin Waugh, Matthew Lai, Edouard Leurent, Nenad Tomasev, Lisa Schut, Demis Hassabis, Satinder Singh

CoRR, 2023

2021

DeDUCE: Generating Counterfactual Explanations Efficiently.

Benedikt Höltgen, Lisa Schut, Jan Markus Brauner, Yarin Gal

CoRR, 2021

Speedy Performance Estimation for Neural Architecture Search.

Robin Ru, Clare Lyle, Lisa Schut, Miroslav Fil, Mark van der Wilk, Yarin Gal

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties.

Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search.

Binxin Ru, Clare Lyle, Lisa Schut, Mark van der Wilk, Yarin Gal

CoRR, 2020

Capsule Networks - A Probabilistic Perspective.

Lewis Smith, Lisa Schut, Yarin Gal, Mark van der Wilk

CoRR, 2020

A Bayesian Perspective on Training Speed and Model Selection.

Clare Lyle, Lisa Schut, Binxin Ru, Yarin Gal, Mark van der Wilk

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020