Microprocessor Architecture for a Changing World: The Motorola 68000. - Edward Stritter; Tom Gunter (Computer, 1979)

Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. - Tom Gunter; Michael A. Osborne; Roman Garnett; Philipp Hennig; Stephen J. Roberts (NIPS, 2014)

Efficient Bayesian Nonparametric Modelling of Structured Point Processes. - Tom Gunter; Chris M. Lloyd; Michael A. Osborne; Stephen J. Roberts (UAI, 2014)

Variational Inference for Gaussian Process Modulated Poisson Processes. - Chris M. Lloyd; Tom Gunter; Michael A. Osborne; Stephen J. Roberts (ICML, 2015)

Latent Point Process Allocation. - Chris M. Lloyd; Tom Gunter; Michael A. Osborne; Stephen J. Roberts; Tom Nickson (AISTATS, 2016)

Unknowable Manipulators: Social Network Curator Algorithms. - Samuel Albanie; Hillary Shakespeare; Tom Gunter (CoRR, 2017)

Towards efficient Bayesian inference: Cox processes and probabilistic integration. - Tom Gunter (2017)

Masked Autoencoding Does Not Help Natural Language Supervision at Scale. - Floris Weers; Vaishaal Shankar; Angelos Katharopoulos; Yinfei Yang; Tom Gunter (CVPR, 2023)

STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. - Chen Chen 005; Bowen Zhang 002; Liangliang Cao; Jiguang Shen; Tom Gunter; Albin Madappally Jose; Alexander Toshev; Yantao Zheng; Jonathon Shlens; Ruoming Pang; Yinfei Yang (EMNLP, 2023)

Self Supervision Does Not Help Natural Language Supervision at Scale. - Floris Weers; Vaishaal Shankar; Angelos Katharopoulos; Yinfei Yang; Tom Gunter (CoRR, 2023)

STAIR: Learning Sparse Text and Image Representation in Grounded Tokens. - Chen Chen 005; Bowen Zhang 002; Liangliang Cao; Jiguang Shen; Tom Gunter; Albin Madappally Jose; Alexander Toshev; Jonathon Shlens; Ruoming Pang; Yinfei Yang (CoRR, 2023)

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts. - Erik A. Daxberger; Floris Weers; Bowen Zhang 002; Tom Gunter; Ruoming Pang; Marcin Eichner; Michael Emmersberger; Yinfei Yang; Alexander Toshev; Xianzhi Du (CoRR, 2023)

MM1: Methods, Analysis and Insights from Multimodal LLM Pre-training. - Brandon McKinzie; Zhe Gan; Jean-Philippe Fauconnier; Sam Dodge; Bowen Zhang 002; Philipp Dufter; Dhruti Shah; Xianzhi Du; Futang Peng; Anton Belyi; Haotian Zhang 005; Karanjeet Singh 003; et al. (ECCV (29), 2024)

MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training. - Brandon McKinzie; Zhe Gan; Jean-Philippe Fauconnier; Sam Dodge; Bowen Zhang 002; Philipp Dufter; Dhruti Shah; Xianzhi Du; Futang Peng; Floris Weers; Anton Belyi; Haotian Zhang 005; et al. (CoRR, 2024)

Revisiting MoE and Dense Speed-Accuracy Comparisons for LLM Training. - Xianzhi Du; Tom Gunter; Xiang Kong; Mark Lee; Zirui Wang; Aonan Zhang; Nan Du; Ruoming Pang (CoRR, 2024)

Large Language Model-guided Document Selection. - Xiang Kong; Tom Gunter; Ruoming Pang (CoRR, 2024)

Apple Intelligence Foundation Language Models. - Tom Gunter; Zirui Wang; Chong Wang; Ruoming Pang; Andy Narayanan; Aonan Zhang; Bowen Zhang 002; Chen Chen 005; Chung-Cheng Chiu; David Qiu; Deepak Gopinath; Dian Ang Yap; et al. (CoRR, 2024)

Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge? - Arduin Findeis; Floris Weers; Guoli Yin; Ke Ye; Ruoming Pang; Tom Gunter (ACL (1), 2025)

Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality. - Alex Fang; Hadi Pouransari; Matt Jordan; Alexander Toshev; Vaishaal Shankar; Ludwig Schmidt; Tom Gunter (CoRR, 2025)

AXLearn: Modular Large Model Training on Heterogeneous Infrastructure. - Mark Lee; Tom Gunter; Chang Lan; John Peebles; Hanzhi Zhou; Kelvin Zou; Sneha Bangalore; Chung-Cheng Chiu; Nan Du; Xianzhi Du; Philipp Dufter; Ruixuan Hou; et al. (CoRR, 2025)

Language Models Improve When Pretraining Data Matches Target Tasks. - David Mizrahi; Anders Boesen Lindbo Larsen; Jesse Allardice; Suzie Petryk; Yuri Gorokhov; Jeffrey Li; Alex Fang; Josh Gardner 001; Tom Gunter; Afshin Dehghan (CoRR, 2025)

Apple Intelligence Foundation Language Models: Tech Report 2025. - Hanzhi Zhou; Erik Hornberger; Pengsheng Guo; Xiyou Zhou; Saiwen Wang; Xin Wang; Yifei He; Xuankai Chang; Rene Rauch; Louis D'hauwe; John Peebles; Alec Doane; et al. (CoRR, 2025)