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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Epistemic and Aleatoric Uncertainty in Machine Learning
Published:
Uncertainty; Epistemic Uncertainty; Aleatoric Uncertainty; ML.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Faithful Knowledge Distillation [Preprint]
Published in Arxiv, 2023
Knowledge distillation; verification; robustness
Recommended citation: Lamb, Tom A., et al. "Faithful Knowledge Distillation." arXiv preprint arXiv:2306.04431 (2023). https://arxiv.org/abs/2306.04431
Universal In-Context Approximation By Prompting Fully Recurrent Models
Published in NeurIPS, 2024
LLMs; steering; spurious correlations
Recommended citation: Petrov, A., Lamb, T., Paren, A., Torr, P. and Bibi, A., 2024. Universal in-context approximation by prompting fully recurrent models. Advances in Neural Information Processing Systems, 37, pp.72061-72093. https://proceedings.neurips.cc/paper_files/paper/2024/file/848784373188ddf641079524e89e0ac9-Paper-Conference.pdf
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models
Published in NeurIPS Track on Datasets and Benchmarks., 2024
LLMs; steering; spurious correlations
Recommended citation: Hemmat, Arshia, et al. "Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models." The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https://arxiv.org/abs/2411.06287
Focus on this, not that! Steering LLMs with Adaptive Feature Specification
Published in ICML, 2025
LLMs; steering; spurious correlations
Recommended citation: Lamb, Tom A., et al. "Focus On This, Not That! Steering LLMs with Adaptive Feature Specification." Forty-second International Conference on Machine Learning. https://openreview.net/pdf?id=rbI5mOUA8Z
Semantic-Level Confidence Calibration of Language Models via Temperature Scaling
Published in ICLR: QUESTION Workshop, 2025
LLMs; Uncertiainty Quantification; Semantic Calibration
Recommended citation: Lamb, T. A., Ivanova, D. R., Torr, P., & Rudner, T. G. (2025). Semantic-Level Confidence Calibration of Language Models via Temperature Scaling. In ICLR Workshop: Quantify Uncertainty and Hallucination in Foundation Models: The Next Frontier in Reliable AI. https://openreview.net/pdf?id=22UNXHzBgt
resources
Summer Mathematics Research Work: Polylogarithmic Integral Identities
Published:
MZVs; Polylogarithms
MMath Dissertation: An Introduction to Modular Forms and the Eichler-Shimura Isomorphism
Published:
Modular Forms; Hecke Operators; L-Functions; Eichler-Shimura Isomorphism
MSc Dissertation: Self-Supervised Learning of Tractable Generative Models
Published:
Probabilistic Circuits; EiNets; Probabilistic Models; CCLE
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.