1/ Chain of thought reasoning can be significantly improved using RLVR but can we improve the generation process for reasoning tokens during training for better exploration, efficiency and performance? @brendanh0gan and I explore this question in our recent work 🧵 (tldr: yes!)
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Very cool work!
We’re excited to introduce ShinkaEvolve: An open-source framework that evolves programs for scientific discovery with unprecedented sample-efficiency. Blog: sakana.ai/shinka-evolve/ Code: github.com/SakanaAI/Shink… Like AlphaEvolve and its variants, our framework leverages LLMs to…
My acceptance speech at the Turing award ceremony: Good evening ladies and gentlemen. The main idea of reinforcement learning is that a machine might discover what to do on its own, without being told, from its own experience, by trial and error. As far as I know, the first…
Gemma-3 270M has interesting collapse behavior - it uses words from different indian languages - Hindi, Tamil, Marathi, Bangla (the task is english based) - perhaps a multi-lingual pretraining quirk?
introducing qqWen: our fully open-sourced project (code+weights+data+detailed technical report) for full-stack finetuning (pretrain+SFT+RL) a series of models (1.5b, 3b, 7b, 14b & 32b) for a niche financial programming language called Q All details below!
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