research
FlyThinker: Researchers propose parallel reasoning during generation for personalized responses
Researchers introduce FlyThinker, a framework that runs reasoning and generation concurrently rather than sequentially, addressing limitations of existing "think-then-generate" approaches in long-form personalized text generation. The method uses a separate reasoning model that generates token-level guidance in parallel with the main generation model, enabling more adaptive reasoning without sacrificing computational efficiency.