| 02/07/26 | Memory in LLMs | David Blackwell | Alex Hickey |
| 25/06/26 | Hybrid Architectures | David Blackwell | Fede |
| 18/06/26 | Self-Adapting Language Models & others | David Blackwell | Fede |
| 26/03/26 | The Smol Training Playbook: The Secrets to Building World-Class LLMs | David Blackwell | Fede |
| 19/03/26 | Reasoning Models Generate Societies of Thought | David Blackwell | Ed Gunn |
| 10/02/26 | Dropout as a Bayesian Approximation | David Blackwell | Alex Hickey |
| 22/01/26 | LLM inference engine building | Enigma | Fede |
| 20/11/25 | DeepSeek OCR | David Blackwell | Fede & Rosie |
| 06/11/25 | Continual Learning via Sparse Memory Finetuning | Margaret Hamilton | Fede |
| 30/10/25 | LLMs for Audio-Visual Speech Recognition | David Blackwell | Phil Swatton |
| 23/10/25 | Agentic Context Engineering | David Blackwell | Fede |
| 22/09/25 | On the Theoretical Limitations of Embedding-Based Retrieval | David Blackwell | Fede & Alex |
| 02/06/25 | Enrichment Students Project Presentations | Margaret Hamilton | Sandrine Chausson & Yara Kyrychenko |
| 28/05/25 | Improving Factuality and Reasoning in Language Models through Multiagent Debate | Jack Good | Fede |
| 21/05/25 | Test-Time Reinforcement Learning | David Blackwell | Fede |
| 12/05/25 | Event Extaction with LLMs | David Blackwell | Alex Hickey |
| 07/04/25 | Enrichment Students project talk | David Blackwell | Sushant Gautam & Yara Kyrychenko |
| 24/03/25 | S1: Simple test-time scaling | David Blackwell | Fede |
| 03/03/25 | Alignment reduces LLMs conceptual diversity | David Blackwell | Fede |
| 17/02/25 | DeepSeek-V3 Technical Report (part 2) | Florence Nightingale | Fede |
| 10/02/25 | DeepSeek-V3 Technical Report: Group Discussion | David Blackwell | Fede & Ryan |
| 03/02/25 | DeepSeek-R1: Group Discussion | David Blackwell | Fede & Ryan |
| 16/12/24 | Improving training with better learning rate and batch size: Linear scaling rule from random matrix theory (Slides) | David Blackwell | Chanju Park |
| 09/12/24 | Scaling laws of neural networks (Slides) | David Blackwell | Edmund Dable-Heath |
| 03/12/24 | Mechanistic Interpretability | Enigma | Neel Nanda |
| 02/12/24 | Diffusion models | Ada Lovelace | James Thornton |
| 02/12/24 | Can language models play the Wikipedia game? (Slides) | David Blackwell | Alex Hickey, Jo Knight |
| 25/11/24 | Application of foundation models in time series tasks | David Blackwell | Gholamali Aminian |
| 20/11/24 | Mechanistic Interpretability III (Slides) | Delilah | Ryan Chan |
| 18/11/24 | Biological neural networks (Slides, Slides) | David Blackwell | Balázs Mészáros , Jess Yu |
| 04/11/24 | Invited Talk: Ethnographic Approaches to AI Evaluations | Ursula Franklin | Jonas Kgomo |
| 28/10/24 | No Language Left Behind (NLLB) Technical Report Overview (Slides) | David Blackwell | Giulia Occhini, Ryan Chan |
| 14/10/24 | Invited Talk: Causal Estimation of Memorisation Profiles (Slides) | David Blackwell | Pietro Lesci |
| 07/10/24 | Invited Talk: Federating Large Language Models from Scratch (Slides) | David Blackwell | Lorenzo Sani |
| 02/10/24 | Mechanistic Interpretability II (Slides) | Delilah | Ryan Chan |
| 23/09/24 | Mechanistic Interpretability I (Slides) | David Blackwell | Ryan Chan |
| 09/09/24 | Invited Talk: On the Brittleness of Prompts in LLMs (Slides) | David Blackwell | Han Zhou |
| 03/09/24 | Invited Talk: Sociotechnical Safety Evaluation of AI systems (Slides) | Enigma | Laura Weidinger |
| 28/08/24 | Mixture of Experts (Slides) | Jack Good | Angus R Williams |
| 19/08/24 | Overview of Knowledge Graphs (Slides) | David Blackwell | Navdeep Kaur |
| 12/08/24 | Llama 3.1 Report Overview (Slides) | Ursula Franklin | Edwin Brown, Ryan Chan |
| 05/08/24 | Invited Talk: The growth of parallelism in machine learning inference (Slides) | Ursula Franklin | Tim Harris (Microsoft) |
| 22/07/24 | Invited Talk: Designing a Value-driven GAI Framework for Social Good: Embedding Social Good Values into GAI Models (Slides) | Ursula Franklin | Victor OK Li, Jacqueline CK Lam and Jon Crowcroft |
| 15/07/24 | Invited Talk: Open science projects for open-source models and transparent open datasets | Cipher | Christopher Klamm |
| 08/07/24 | Invited Talk: Equally Safe Online? A participatory approach to tackling Gender-Based Violence (Slides) | David Blackwell | Gavin Abercrombie |
| 01/07/24 | A perspective on the fundamentals of transformers (Slides) | Ursula Franklin | Ed Gunn |
| 04/06/24 | Invited Talk: Are we ready for attacks on machine learning? | Enigma (2.30pm) | Nicholas Carlini |
| 20/05/24 | KAN: Kolmogorov-Arnold Networks | Ursula Franklin | Andrew Duncan |
| 13/05/24 | Overview of LLM Security (Slides) | David Blackwell | Ed Chapman, Burak Hasircioglu, Ezzeldin Zaki |
| 29/04/24 | Invited Talk: How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions (Slides) | David Blackwell | Lorenzo Pacchiardi |
| 22/04/24 | Research at Turing: Learn how to learn and distil during learning - Using meta-learning and second order optimisation to prune the model | David Blackwell | Yilei Liang |
| 15/04/24 | Research at Turing: Natural Logic-based Fact Verification with LLMs | David Blackwell | Marek Strong |
| 08/04/24 | Paper overviews (Slides, Slides) | Ursula Franklin | Fede Nanni, Markus Hauru, Praveen Selvaraj |
| 18/03/24 | Research at Turing: Not even a Chinese Room: evaluating LLMs on code simulation | David Blackwell | Emanuele La Malfa |
| 11/03/24 | Research at Turing: Applying Vision Transformers in Neuroscience (Slides) | David Blackwell | Bryan Li |
| 04/03/24 | Discussion: Expanding participatory governance for LLMs: case studies from BigCode, Aya Initiative, and Collective Intelligence Project (Slides) | David Blackwell | Jennifer Ding |
| 26/02/24 | Research at Turing: Machine translation quality estimation (Slides) | David Blackwell | Radka Jersakova, Jo Knight |
| 19/02/24 | Research at Turing: Longitudinal NLP (Slides) | David Blackwell | Jenny Chim, Talia Tseriotou |
| 12/02/24 | Mechanistic interpretability (Slides) | David Blackwell | Praveen Selvaraj |
| 05/02/24 | Discussion: Existential Risk of AI? (Slides) | David Blackwell | Levan Bokeria |
| 29/01/24 | Vision Transformers Need Registers (Slides) | David Blackwell | Tom Davies |
| 22/01/24 | Research at Turing: Spatial Graph Patterning of Filamentous Structures | David Blackwell | Kristina Ulicna |
| 15/01/24 | Retentive Networks (Slides) | David Blackwell | Ed Gunn |
| 08/01/24 | Discussion: Benchmarking AI applications on GPUs (Slides) | David Blackwell | Tomas Lazauskas, David Llewellyn-Jones |
| 11/12/23 | Stable Diffusion (Slides) | David Blackwell | Edmund Dable-Heath |
| 04/12/23 | Discussion: Best Practice for Responsible Foundation Models – What Should Developers Do and How You Can Help (Slides) | Ursula Franklin | Carolyn Ashurst |
| 20/11/23 | Research at Turing: Transformers for coding/software engineering (Slides) | Mae Jemison | Anastasiia Grishina |
| 13/11/23 | Introduction to Diffusion models (Slides) | David Blackwell | Edmund Dable-Heath |
| 06/11/23 | Discussion: Current challenges and future directions in safety evaluations for generative AI (Slides) | David Blackwell | Jonathan Bright |
| 30/10/23 | Knowledge retrieval (Slides) | David Blackwell | Praveen Selvaraj |
| 16/10/23 | Prompt Engineering (Slides) | David Blackwell | Martin Stoffel |
| 02/10/23 | Reinforcement Learning Human Feedback (RLHF) (Slides) | David Blackwell | Eseoghene Ben-Iwhiwhu |
| 25/09/23 | LoRA (+ parameter efficient fine-tuning) part II (Notebook) | Margaret Hamilton | Jack Roberts |
| 18/09/23 | LoRA (+ parameter efficient fine-tuning) part I (Slides) | David Blackwell | Jack Roberts |
| 21/08/23 | Vision Transformers part II (Slides) | David Blackwell | Katie Awty-Carroll |
| 07/08/23 | Vision Transformers part I (Slides) | David Blackwell | Katie Awty-Carroll, Ryan Chan |
| 24/07/23 | GPT: Pretraining Decoders (Slides) | David Blackwell | Ryan Chan |
| 10/07/23 | BERT: Masked Language modelling and Pre-training (Slides) | David Blackwell | Ryan Chan |
| 26/06/23 | Attention (continued) (Slides) & Transformer Encoder and Decoders (Slides) | David Blackwell | Martin Stoffel, Ryan Chan |
| 31/05/23 | Reginald overview & Attention and self-attention networks (Notebook) | David Blackwell | Evelina Gabasova, Martin Stoffel |
| 15/05/23 | Hands-on RNN/LSTM session (Materials) | David Blackwell | Nathan Simpson, Levan Bokeria, David Llewellyn-Jones |
| 03/05/23 | Sequence-to-sequence models part II: Encoder-decoder models (Slides) | David Blackwell | Ryan Chan |
| 17/04/23 | Sequence-to-sequence models part I: RNNs/LSTMs (Slides) | David Blackwell | Ryan Chan |
| 03/04/23 | Deep Learning Basics (Slides) | David Blackwell | Phil Swatton, Jack Roberts |
| 20/03/23 | Introduction to word embeddings and language modelling (Slides) | David Blackwell | Fede Nanni |
