5 papers
Generative UI: LLMs are Effective UI Generators
Yaniv Leviathan, Dani Valevski, Matan Kalman +10
AI models excel at creating content, but typically render it with static, predefined interfaces. Specifically, the output of LLMs is often a markdown "wall of text". Generative UI…
Prompt Repetition Improves Non-Reasoning LLMs
Yaniv Leviathan, Matan Kalman, Yossi Matias
When not using reasoning, repeating the input prompt improves performance for popular models (Gemini, GPT, Claude, and Deepseek) without increasing the number of generated tokens o…
Selective Attention Improves Transformer
Yaniv Leviathan, Matan Kalman, Yossi Matias
Unneeded elements in the attention's context degrade performance. We introduce Selective Attention, a simple parameter-free change to the standard attention mechanism which reduces…
Diffusion Models Are Real-Time Game Engines
Dani Valevski, Yaniv Leviathan, Moab Arar +1
We present GameNGen, the first game engine powered entirely by a neural model that also enables real-time interaction with a complex environment over long trajectories at high qual…
Block Verification Accelerates Speculative Decoding
Ziteng Sun, Uri Mendlovic, Yaniv Leviathan +4
Speculative decoding is an effective method for lossless acceleration of large language models during inference. It uses a fast model to draft a block of tokens which are then veri…