5 papers
MEMENTO: Teaching LLMs to Manage Their Own Context
Vasilis Kontonis, Yuchen Zeng, Shivam Garg +7
Reasoning models think in long, unstructured streams with no mechanism for compressing or organizing their own intermediate state. We introduce MEMENTO: a method that teaches model…
Phi-4-reasoning-vision-15B Technical Report
Jyoti Aneja, Michael Harrison, Neel Joshi +3
We present Phi-4-reasoning-vision-15B, a compact open-weight multimodal reasoning model, and share the motivations, design choices, experiments, and learnings that informed its dev…
Dion2: A Simple Method to Shrink Matrix in Muon
Kwangjun Ahn, Noah Amsel, John Langford
The Muon optimizer enjoys strong empirical performance and theoretical grounding. However, the super-linear cost of its orthonormalization step introduces increasing overhead with…
Dion: Distributed Orthonormalized Updates
Kwangjun Ahn, Byron Xu, Natalie Abreu +5
Orthonormalized updates accelerate training, improve stability, and enable robust hyperparameter transfer, but existing methods like Muon rely on dense matrix operations that clash…
Efficient Joint Prediction of Multiple Future Tokens
Kwangjun Ahn, Alex Lamb, John Langford
In this short report, we introduce joint multi-token prediction (JTP), a lightweight modification of standard next-token prediction designed to enrich hidden state representations…