Donghua University’s five-agent AI system cross-checks muscle signals against facial expressions and verbal reports to configure personalized rehabilitation braces — catching cases where patients exaggerate, suppress, or simply can’t articulate their discomfort accurately. It achieves 0.88 parameter accuracy versus 0.13…
DeepSeek R1 made two things obvious to anyone paying attention. Reinforcement learning can pull genuinely new reasoning behavior out of a language model that supervised training alone never produces, and distilling from a strong reasoning model is often the faster,…
KDRL Unifies Distillation And Reinforcement Learning Read More »
Large language models keep getting better, but that improvement comes bundled with a cost problem. A model with billions of parameters needs serious hardware just to run, which rules it out for a lot of practical deployment settings, particularly anything…
POCL: How A Progressive Overload Curriculum Improves LLM Distillation Read More »