@dair_ai
Nice primer on post-training reasoning data. (bookmark it) This is one of the first primers to pull the scattered post-training reasoning-data literature into one place, synthesizing over 150 public studies and system reports that previously lived across dataset papers, RL recipes, reward-model studies, benchmarks, and frontier reports. It organizes everything around four questions. What data objects exist, what makes them useful, how they are constructed, and how they scale. Paper: https://t.co/royylAHk3y Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c