3 citations · 3 across the 4 of their papers we have counts for
4 papers
Test-Time Alignment of Text-to-Image Diffusion Models via Null-Text Embedding Optimisation
Taehoon Kim, Henry Gouk, Timothy Hospedales
Test-time alignment (TTA) aims to adapt models to specific rewards during inference. However, existing methods tend to either under-optimise or over-optimise (reward hack) the targ…
Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning
Taehoon Kim, Henry Gouk, Minyoung Kim +1
Certifying the IID generalisation ability of deep networks is the first of many requirements for trusting AI in high-stakes applications from medicine to security. However, when in…
Future-Proof Yourself: An AI Era Survival Guide
Taehoon Kim
Future-Proof Yourself is a practical guide that helps readers navigate the fast-changing world of artificial intelligence in everyday life. The book begins by explaining how comput…
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning
Taehoon Kim, Pyunghwan Ahn, Sangyun Kim +39
In this report, we introduce NICE (New frontiers for zero-shot Image Captioning Evaluation) project and share the results and outcomes of 2023 challenge. This project is designed t…