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Anonymisation in egocentric video
A video digest of research related to anonymisation in egocentric video.
Topics: computer vision, privacy
Date: April, 2022
[slides]
Neural network architectures, scaling laws and transformers
Summary: A video digest of ideas related to neural network architectures, scaling laws and transformers.
Topics: neural network architectures, scaling laws, transformers
Date: April, 2022
[slides]
Contrastive Language-Image Pre-training (CLIP)
Summary: A video digest of the CLIP research paper.
Topics: computer vision, zero-shot learning, vision and language
Date: April, 2022
[slides]
Self-supervised learning and pseudo-labelling
Summary: A video digest of research ideas related to self-supervised learning and the pseudo-labelling algorithm.
Topics: computer vision, self-supervised learning, pseudo-labelling
Date: April, 2022
[slides]
Flamingo: a Visual Language Model for Few-Shot Learning
Summary: A video digest of the Flamingo research paper.
Topics: computer vision, few-shot learning, vision and language
Date: May, 2022
[slides]
DINO: Self-distillation with no labels
Summary: A video digest of the DINO research paper.
Topics: computer vision, few-shot learning, vision and language
Date: June, 2022
[slides]
Querybank normalisation (QB-Norm)
Summary: A video digest of the QB-Norm research paper.
Topics: vision and language, hubness, cross modal retrieval
Date: June, 2022
[slides]
On the Opportunities and Risks of Foundation Models (introduction)
Summary: A slow video description of the introduction to the Foundation Models report from Stanford.
Topics: foundation models, emergence, homogenisation
Date: June, 2022
[slides]
Language Models are Few-shot Learners (GPT-3)
Summary: A slow video description of the GPT-3 research paper.
Topics: language models, foundation models, GPT-3, scaling
Date: July, 2022
[slides]
Evaluating Large Language Models Trained on Code (Codex)
Summary: A slow video description of the Codex research paper.
Topics: codex, language models, foundation models, coding
Date: July, 2022
[slides]
Why numbering should start at zero (according to Dijkstra): Samuel’s guide
Summary: Samuel's tutorial on Why numbering should start at zero by Edsger W. Dijkstra, published in 1982 as EWD 831.
Topics: Dijkstra, counting, programming conventions
Date: September, 2022
[slides]
Row-major vs column-major: Samuel’s guide
Summary: Samuel's tutorial on row-major and column-major ordering for multi-dimensional array storage.
Topics: computing, memory, arrays
Date: September, 2022
[slides]
🤗 Datasets: A community library for natural language processing
Summary: A description of the 🤗 Datasets library, as summarised by Q. Lhoest et al. in their EMNLP 2021 demo paper.
Topics: Hugging Face, machine learning, NLP
Date: September, 2022
[slides]
PromptSource - an IDE and repo for natural language prompts
Summary: A description of PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts by S. Bach and others under the BigScience project as a demo at ACL 2022.
Topics: Prompting, annotation tools, NLP
Date: September, 2022
[slides]
Hash tables: Samuel’s guide
Summary: Samuel's tutorial on the hash table data structure.
Topics: Hash tables, data structures, algorithms, coding
Date: September, 2022
[slides]
Big O notation: Samuel’s guide
Summary: Samuel's tutorial on big O notation and other asymptotic notation (little o, big theta, big omega, little omega).
Topics: Complexity, data structures, algorithms, analysis
Date: October, 2022
[slides]
ReCo: Retrieve and Co-segment for Zero-Shot Transfer
Summary: A short description of the ReCo framework introduced in the work 'ReCo: Retrieve and Co-segment for Zero-shot Transfer' by G. Shin, W. Xie and S. Albanie, published at NeurIPS in 2022.
Topics: semantic segmentation, foundation models, zero shot transfer
Date: October, 2022
[slides]
Scaling Instruction-Finetuned Language Models (Flan-PaLM)
Summary: A description of the the work 'Scaling Instruction-Finetuned Language Models' by Hyung Won Chung et al. published on arxiv in October 2022. This work introduced the Flan-PaLM 540B model.
Topics: instruction finetuning, foundation models, large language models
Date: October, 2022
[slides]
Binary Search Trees: Samuel’s guide
Summary: Samuel's tutorial on the binary search tree data structure.
Topics: Binary search trees, data structures, algorithms, coding
Date: October, 2022
[slides]
Crosslingual Generalization through Multitask Finetuning (BLOOMZ & mT0)
Summary: A description of the the work 'Crosslingual Generalization through Multitask Finetuning' by Niklas Muennighoff et al. published on arxiv in November 2022 as part of the BigScience Workshop. This work introduced the BLOOMZ and mT0 models.
Topics: multitask finetuning, foundation models, large language models, multilingual models
Date: November, 2022
[slides]
Red-black trees: Samuel’s guide
Summary: Samuel's tutorial on the red-black tree data structure.
Topics: Red-black trees, data structures, algorithms, coding
Date: December, 2022
[slides]
B-trees: Samuel’s guide
Summary: Samuel's tutorial on the B-tree data structure.
Topics: B-trees, data structures, algorithms, coding
Date: December, 2022
[slides]
Heapsort and Binary Heaps: Samuel’s guide
Summary: Samuel's tutorial on Heapsort and the binary heap data structure.
Topics: Heapsort, binary heap, priority queue, data structures, algorithms, coding
Date: December, 2022
[slides]
Quicksort: Samuel’s tutorial
Summary: Samuel's tutorial on the quicksort algorithm.
Topics: Quicksort, sorting, algorithms, coding
Date: January, 2023
[slides]
Comparison Sorting Lower Bounds: Samuel’s tutorial
Summary: Samuel's tutorial on lower bounds on the fastest possible comparison sorting algorithms.
Topics: lower bounds, sorting, algorithms, coding
Date: January, 2023
[slides]
Counting Sort: Samuel’s tutorial
Summary: Samuel's tutorial on counting sort.
Topics: sorting, algorithms, coding
Date: January, 2023
[slides]
Radix Sort: Samuel’s tutorial
Summary: Samuel's tutorial on counting sort.
Topics: radix sort, sorting, algorithms, coding
Date: January, 2023
[slides]
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Summary: A description of the the work 'BLOOM: A 176B-Parameter Open-Access Multilingual Language Model' by Le Scao et al. published on arxiv in November 2022 as part of the BigScience Workshop. This work provides an overview of the BLOOM model and the efforts involved in its creation.
Topics: foundation models, large language models, multilingual models
Date: January, 2023
[slides]
Bucket Sort: Samuel’s tutorial
Summary: Samuel's tutorial on bucket sort.
Topics: bucket sort, sorting, algorithms, coding
Date: January, 2023
[slides]
Task-parallel computing: Samuel’s tutorial
Summary: Samuel's tutorial on task-parallel computing.
Topics: Task parallelism, data parallelism, Moore's law, Dennard scaling, Amdahl's law, Gustafson's law
Date: February, 2023
[slides]
What is the alignment problem?
Summary: A short description of What is the alignment problem? by Jan Leike.
Topics: AI alignment, capabilities, the hard problem of alignment
Date: March, 2023
[slides]
NP-complete problems: Samuel’s tutorial
Summary: Samuel's tutorial on NP-complete problems.
Topics: P versus NP, decision problems, verification algorithms, NP-completeness
Date: February, 2023
[slides]
GPT-4
Summary: A description of the GPT-4 technical report by OpenAI.
Topics: GPT-4, Large Language Model, Capabilities, Risks
Date: March, 2023
[slides]
Large Language Models are Few-Shot Publication Scoopers
Summary: A summary of the SIGBOVIK 2023 paper, Large Language Models are Few-Shot Publication Scoopers.
Topics: Scooping, Large Language Models, SIGBOVIK
Date: March, 2023
[slides]
Computer Vision: A very short introduction
Summary: A very short introduction to the field of computer vision.
Topics: Computer Vision, introduction, tasks
Date: April, 2023
[slides]
AI News (24th April 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: April, 2023
[slides]
AI News (1st May 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: May, 2023
[slides]
AI News (8th May 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: May, 2023
[slides]
AI News (15th May 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: May, 2023
[slides]
AI News (24th May 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: May, 2023
[slides]
AI News (31st May 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: May, 2023
[slides]
AI News (5th June 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: June, 2023
[slides]
AI News (12th June 2023)
Summary: A short summary of recent AI-related news.
Topics: AI news
Date: June, 2023
[slides]
Vision Transformer Basics
Summary: A lecture covering the basics of vision transformers.
Topics: Transformers
Date: November, 2023
[slides]
Self-supervised Vision
Summary: A lecture covering the basics of self-supervision in Computer Vision.
Topics: Self-supervised learning
Date: November, 2023
[slides]
Gemini: A Family of Highly Capable Multimodal Models
Summary: A summary of the Google DeepMind Gemini tech report.
Topics: Gemini, Foundation models
Date: December, 2023
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Summary: A summary of the Mamba architecture.
Topics: Mamba, Foundation models
Date: December, 2023
research
Up-To-Date Malaria Mapping : Prediction From Remote Imagery
Samuel Albanie and Stephen J. Roberts
Technical Report, 2015
paper
Learning Grimaces by Watching TV
Samuel Albanie and Andrea Vedaldi
Proceedings of the British Machine Vision Conference (BMVC), 2016
paper
Unknowable Manipulators: Social Network Curator Algorithms
Samuel Albanie and Hillary Shakespeare and Tom Gunter
Machine Learning and the Law, NeurIPS Symposium, 2016
paper
Seeing Voices and Hearing Faces: Cross-Modal Biometric Matching
Arsha Nagrani and Samuel Albanie and Andrew Zisserman
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018
paper, project page
CVPR spotlight
Self-Supervised Learning of Geometrically Stable Features Through Probabilistic Introspection
David Novotny* and Samuel Albanie* and Diane Larlus and Andrea Vedaldi
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2018
paper
CVPR spotlight
Learnable PINs: Cross-Modal Embeddings for Person Identity
Arsha Nagrani* and Samuel Albanie* and Andrew Zisserman
European Conference on Computer Vision (ECCV), 2018
paper, project page
Semi-convolutional Operators for Instance Segmentation
David Novotny* and Samuel Albanie* and Diane Larlus and Andrea Vedaldi
European Conference on Computer Vision (ECCV), 2018
paper
Emotion Recognition in Speech using Cross-Modal Transfer in the Wild
Samuel Albanie* and Arsha Nagrani* and Andrea Vedaldi and Andrew Zisserman
Proceedings of the 26th ACM international conference on Multimedia (ACM MM), 2018
paper, project page, code
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
Jie Hu and Li Shen and Samuel Albanie and Gang Sun and Andrea Vedaldi
Advances in Neural Information Processing Systems (NeurIPS), 2018
paper, code
Squeeze-and-Excitation Networks
Jie Hu and Li Shen and Samuel Albanie and Gang Sun and Enhua Wu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
paper, code
Use What You Have: Video retrieval using representations from collaborative experts
Yang Liu* and Samuel Albanie* and Arsha Nagrani* and Andrew Zisserman
Proceedings of the British Machine Vision Conference (BMVC), 2019
paper, project page, code
Note: includes a correction to initially results (details on project page). We thank Valentin Gabeur for identifying the issue.
Small Steps and Giant Leaps: Minimal Newton Solvers for Deep Learning
João F. Henriques and Sébastien Ehrhardt and Samuel Albanie and Andrea Vedaldi
IEEE/CVF International Conference on Computer Vision (ICCV), 2019
paper, project page, code
Unsupervised Learning of Landmarks by Descriptor Vector Exchange
James Thewlis* and Samuel Albanie* and Hakan Bilen and Andrea Vedaldi
IEEE/CVF International Conference on Computer Vision (ICCV), 2019
paper, project page
Disentangled Speech Embeddings Using Cross-Modal Self-Supervision
Arsha Nagrani* and Joon Son Chung* and Samuel Albanie* and Andrew Zisserman
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
paper, project page
BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues
Samuel Albanie and Gül Varol and Liliane Momeni and Triantafyllos Afouras and Joon Son Chung and Neil Fox and Andrew Zisserman
European Conference on Computer Vision, 2020
paper, project page, code
Seeing wake words: Audio-visual Keyword Spotting
Liliane Momeni and Triantafyllos Afouras and Themos Stafylakis and Samuel Albanie and Andrew Zisserman
Proceedings of the British Machine Vision Conference, 2020
paper, project page, code
Movement change detected by optical flow precedes, but does not predict, tail-biting in pigs
Mona Lilian Vestbjerg Larsen and Lene Juul Pedersen and Sandra A. Edwards and Samuel Albanie and Marian Stamp Dawkins
Livestock Science, 2020
paper
Explaining the Adaptive Generalisation Gap
Diego Granziol and Samuel Albanie and Xingchen Wan and Stephen J. Roberts
ArXiv, 2020
Watch, read and lookup: learning to spot signs from multiple supervisors
Liliane Momeni* and Gül Varol* and Samuel Albanie* and Triantafyllos Afouras and Andrew Zisserman
ACCV, 2020
paper, project page
Oral; Songde Ma Prize (Best Application Paper)
Mind-the-Gap! Unsupervised Domain Adaptation for Text-Video Retrieval
Qingchao Chen* and Yang Liu* and Samuel Albanie
AAAI, 2021
paper
Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval
Yang Liu* and Qingchao Chen* and Samuel Albanie
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
paper
QUERYD: A Video Dataset with High-Quality Text and Audio Narrations
Andreea-Maria Oncescu and João F. Henriques and Yang Liu and Andrew Zisserman and Samuel Albanie
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
paper, project page, code
Sign Language Segmentation with Temporal Convolutional Networks
Katrin Renz and Nicolaj C. Stache and Samuel Albanie and Gül Varol
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
paper, project page, code
Sign Segmentation with Changepoint-Modulated Pseudo-Labelling
Katrin Renz and Nicolaj C. Stache and Neil Fox and Gül Varol and Samuel Albanie
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021
paper, project page, code
Read and Attend: Temporal Localisation in Sign Language Videos
Gül Varol* and Liliane Momeni* and Samuel Albanie* and Triantafyllos Afouras* and Andrew Zisserman
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
paper, project page
Audio Retrieval with Natural Language Queries
Andreea-Maria Oncescu* and A. Sophia Koepke* and João F. Henriques and Zeynep Akata and Samuel Albanie
Interspeech, 2021
paper, project page, code, demo
Shortlisted for best student paper at Interspeech
Aligning Subtitles in Sign Language Videos
Hannah Bull* and Triantafyllos Afouras* and Gül Varol and Samuel Albanie and Liliane Momeni and Andrew Zisserman
Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2021
paper, project page
TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval
Ioana Croitoru* and Simion-Vlad Bogolin* and Marius Leordeanu and Hailin Jin and Andrew Zisserman and Samuel Albanie and Yang Liu
Proceedings of the IEEE International Conference on Computer Visionp (ICCV), 2021
paper, project page, code
Won the Condensed Movies Challenge at ICCV 2021
All you need are a few pixels: semantic segmentation with PixelPick
Gyungin Shin and Weidi Xie and Samuel Albanie
IEEE International Conference on Computer Vision Workshops (ICCVW), 2021
paper, project page, code
Won best paper at ILDAV ICCVW 2021
BOBSL: BBC-Oxford British Sign Language Dataset
Samuel Albanie* and Gül Varol* and Liliane Momeni* and Hannah Bull* and Triantafyllos Afouras and Himel Chowdhury and Neil Fox and Bencie Woll and Rob Cooper and Andrew McParland and Andrew Zisserman
Technical Report, 2021
paper, project page, coverage, BBC R&D coverage
Audio Retrieval with Natural Language Queries: A Benchmark Study
A Koepke* and Andreea-Maria Oncescu* and João F Henriques and Zeynep Akata and Samuel Albanie
Transactions on Multimedia, 2022
paper, project page, code, demo
Extension of Interspeech 2021 paper with a new dataset
Scaling up sign spotting through sign language dictionaries
Gül Varol* and Liliane Momeni* and Samuel Albanie* and Triantafyllos Afouras and Andrew Zisserman
International Journal of Computer Vision, 2022
paper
Quantum Self-Supervised Learning
Ben Jaderberg and Lewis W. Anderson and Weidi Xie and Samuel Albanie and M. Kiffner and Dieter Jaksch
Quantum Science and Technology, 2022
paper
Sign Language Video Retrieval with Free-Form Textual Queries
Amanda Duarte and Samuel Albanie and Xavier Giró-i-Nieto and Gül Varol
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
paper, project page
Cross Modal Retrieval with Querybank Normalisation
Simion-Vlad Bogolin* and Ioana Croitoru* and Hailin Jin and Yang Liu and Samuel Albanie
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
paper, project page, code, video_summary
Unsupervised Salient Object Detection with Spectral Cluster Voting
Gyungin Shin and Samuel Albanie and Weidi Wie
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022
paper, code
Automatic dense annotation of large-vocabulary sign language videos
Liliane Momeni and Hannah Bull and KR Prajwal and Samuel Albanie and Gül Varol and Andrew Zisserman
European Conference on Computer Vision (ECCV), 2022
paper, project page
Crosslingual Generalization through Multitask Finetuning
Niklas Muennighoff and Thomas Wang and Lintang Sutawika and Adam Roberts and Stella Biderman and Teven Le Scao and M Saiful Bari and Sheng Shen and Zheng-Xin Yong and Hailey Schoelkopf and Xiangru Tang and Dragomir Radev and Alham Fikri Aji and Khalid Almubarak and Samuel Albanie and Zaid Alyafeai and Albert Webson and Edward Raff and Colin Raffel
arXiv preprint arXiv:2211.01786, 2022
paper, code, video_summary
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Teven Le Scao and Angela Fan and Christopher Akiki and Ellie Pavlick and Suzana Ilić and Daniel Hesslow and Roman Castagné and Alexandra Luccioni and François Yvon and Matthias Gallé and others
arXiv preprint arXiv:2211.05100, 2022
paper, code
Weakly-supervised Fingerspelling Recognition in British Sign Language Videos
KR Prajwal and Hannah Bull and Liliane Momeni and Samuel Albanie and Gül Varol and Andrew Zisserman
Proceedings of the British Machine Vision Conference (BMVC), 2022
paper
RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection
Hangjie Yuan and Jianwen Jiang and Samuel Albanie and Tao Feng and Ziyuan Huang and Dong Ni and Mingqian Tang
Advances in Neural Information Processing Systems (NeurIPS), 2022
paper
ReCo: Retrieve and Co-segment for Zero-shot Transfer
Gyungin Shin and Weidi Wie and Samuel Albanie
Advances in Neural Information Processing Systems (NeurIPS), 2022
paper, project page, code
DeepMIM: Deep Supervision for Masked Image Modeling
Sucheng Ren and Fangyun Wei and Samuel Albanie and Zheng Zhang and Han Hu
arXiv preprint arXiv:2303.08817, 2023
paper, code
Satin: A multi-task metadataset for classifying satellite imagery using vision-language models
Jonathan Roberts and Kai Han and Samuel Albanie
ICCV Workshop: Towards the Next Generation of Computer Vision Datasets, 2023
paper, project page
Can GPT-4 Perform Neural Architecture Search?
Mingkai Zheng and Xiu Su and Shan You and Fei Wang and Chen Qian and Chang Xu and Samuel Albanie
arXiv preprint arXiv:2304.10970, 2023
paper, code
GPT4GEO: How a Language Model Sees the World's Geography
Jonathan Roberts and Timo Lüddecke and Sowmen Das and Kai Han and Samuel Albanie
NeurIPS Workshop on Foundation Models for Decision Making, 2023
paper, code
Zero-shot Unsupervised Transfer Instance Segmentation
Gyungin Shin and Samuel Albanie and Weidi Xie
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
paper, project page, code
Best paper at CVPRW L3D-IVU
arXiVeri: Automatic table verification with GPT
Gyungin Shin and Weidi Xie and Samuel Albanie
NeurIPS Workshop on AI4Science Workshop, 2023
paper, project page, code
Moment Detection in Long Tutorial Videos
Ioana Croitoru and Simion-Vlad Bogolin and Samuel Albanie and Yang Liu and Zhaowen Wang and Seunghyun Yoon and Hailin Jin and Trung Bui
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
paper, code
RLIPv2: Fast Scaling of Relational Language-Image Pre-training
Hangjie Yuan and Shiwei Zhang and Xiang Wang and Samuel Albanie and Yining Pan and Tao Feng and Jianwen Jiang and Dong Ni and Yingya Zhang and Deli Zhao
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
paper, code
Simple Baselines for Interactive Video Retrieval with Questions and Answers
Kaiqu Liang and Samuel Albanie
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
paper, code
SuS-X: Training-Free Name-Only Transfer of Vision-Language Models
Vishaal Udandarao and Ankush Gupta and Samuel Albanie
IEEE/CVF International Conference on Computer Vision (ICCV), 2023
paper, project page, code
Charting New Territories: Exploring the Geographic and Geospatial Capabilities of Multimodal LLMs
Jonathan Roberts and Timo Lüddecke and Rehan Sheikh and Kai Han and Samuel Albanie
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023
paper
Iterative Averaging in the Quest for Best Test Error
Diego Granziol and Nicholas Baskerville and Xingchen Wan and Samuel Albanie and Stephen J. Roberts
Journal of Machine Learning Research, 2024
paper
Visual Data-Type Understanding does not emerge from Scaling Vision-Language Models
Vishaal Udandarao and Max Burg and Samuel Albanie and Matthias Bethge
International Conference on Learning Representations (ICLR), 2024
paper, code
A SOUND APPROACH: Using Large Language Models to generate audio descriptions for egocentric text-audio retrieval
Andreea-Maria Oncescu and João F Henriques and Andrew Zisserman and Samuel Albanie and A Sophia Koepke
ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
paper
A Tale of Two Languages: Large-Vocabulary Continuous Sign Language Recognition from Spoken Language Supervision
Charles Raude and KR Prajwal and Liliane Momeni and Hannah Bull and Samuel Albanie and Andrew Zisserman and Gül Varol
arXiv preprint arXiv:2405.10266, 2024
Inverse Constitutional AI: Compressing Preferences into Principles
Arduin Findeis and Timo Kaufmann and Eyke Hüllermeier and Samuel Albanie and Robert Mullins
arXiv preprint arXiv:2406.06560, 2024
HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits
Tim Franzmeyer and Aleksandar Shtedritski and Samuel Albanie and Philip Torr and João F Henriques and Jakob N Foerster
Findings of the Association for Computational Linguistics (ACL), 2024
GRAB: A Challenging GRaph Analysis Benchmark for Large Multimodal Models
Jonathan Roberts and Kai Han and Samuel Albanie
arXiv preprint arXiv:2408.11817, 2024
paper, project page, code
Foundational challenges in assuring alignment and safety of large language models
Usman Anwar and Abulhair Saparov and Javier Rando and Daniel Paleka and Miles Turpin and Peter Hase and Ekdeep Singh Lubana and Erik Jenner and Stephen Casper and Oliver Sourbut and others
Transactions on Machine Learning Research, 2024
paper
On scalable oversight with weak LLMs judging strong LLMs
Zachary Kenton and Noah Y Siegel and János Kramár and Jonah Brown-Cohen and Samuel Albanie and Jannis Bulian and Rishabh Agarwal and David Lindner and Yunhao Tang and Noah D Goodman and Rohin Shah
Advances in Neural Information Processing Systems (NeurIPS), 2024
paper, coverage
Featured in quanta magazine.
Efficient Lifelong Model Evaluation in an Era of Rapid Progress
Ameya Prabhu and Vishaal Udandarao and Philip Torr and Matthias Bethge and Adel Bibi and Samuel Albanie
Advances in Neural Information Processing Systems (NeurIPS), 2024
paper, code
SciFIBench: Benchmarking Large Multimodal Models for Scientific Figure Interpretation
Jonathan Roberts and Kai Han and Neil Houlsby and Samuel Albanie
Advances in Neural Information Processing Systems (NeurIPS), 2024
paper, code
A Practitioner's Guide to Continual Multimodal Pretraining
Karsten Roth and Vishaal Udandarao and Sebastian Dziadzio and Ameya Prabhu and Mehdi Cherti and Oriol Vinyals and Olivier Hénaff and Samuel Albanie and Matthias Bethge and Zeynep Akata
Advances in Neural Information Processing Systems (NeurIPS), 2024
paper
No "zero-shot" without exponential data: Pretraining concept frequency determines multimodal model performance
Vishaal Udandarao and Ameya Prabhu and Adhiraj Ghosh and Yash Sharma and Philip HS Torr and Adel Bibi and Samuel Albanie and Matthias Bethge
Advances in Neural Information Processing Systems (NeurIPS), 2024
paper, computerphile video
Featured on computerphile!
teaching
Computer Vision
2021
Summary: A course on image structure and deep learning.
Module: 4F12 (Michaelmas 2021).
Foundation Models
2022
Summary: An introduction to Foundation Models (online course).
Algorithms and data structures
2023
Summary: An introduction to algorithms and data structures.
Module: 4M26 (Lent 2023).
Introduction to Computer Vision
2023
Summary: An introduction to topics in computer vision.
Module: 2P8 (Easter 2023).
Computer Vision
2023
Summary: A short course on Transformers and Self-supervised learning.
Module: 4F12 (Michaelmas 2023).