MMLU-Redux just touched down at #NAACL2025! 🎉 Wish I could be there for our "Are We Done with MMLU?" poster today (9:00-10:30am in Hall 3, Poster Session 7), but visa drama said nope 😅 If anyone's swinging by, give our research some love! Hit me up if you check it out! 👋

We created Approximate Likelihood Matching, a principled (and very effective) method for *cross-tokenizer distillation*! With ALM, you can create ensembles of models from different families, convert existing subword-level models to byte-level and a bunch more🧵

Joining the Generative AI Lab (GAIL, gail.ed.ac.uk) at the University of Edinburgh as a GAIL Fellow! Excited for what's ahead 🤗

🤔How to achieve efficient ICL without storing a huge dataset in one prompt? 💡Mixtures of In-Context Learners (𝗠𝗼𝗜𝗖𝗟): we treat LLMs prompted with subsets of demonstrations as experts and learn a weighting function to optimise the distribution over the continuation (🧵1/n)

I’ll be travelling to London from Wednesday to Friday for an upcoming event and would be very happy to meet up! 🚀 I'd love to chat about my recent works (DeCoRe, MMLU-Redux, etc.). DM me if you’re around! 👋 DeCoRe: arxiv.org/abs/2410.18860 MMLU-Redux: arxiv.org/abs/2406.04127