fromHackernoon1 year agoArtificial intelligenceBatched Prompting for Efficient GPT-4 Annotatio | HackerNoonThe article discusses an experiment on Direct Nash Optimization methodologies using reinforcement learning from human feedback (RLHF) for preference modeling.
fromHackernoon1 year agoRoam ResearchUnderstanding Concentrability in Direct Nash Optimization | HackerNoonThe article discusses new theoretical insights in reinforcement learning, particularly in Reward Models and Nash Optimization.
fromHackernoon1 year agoArtificial intelligenceBatched Prompting for Efficient GPT-4 Annotatio | HackerNoon
fromHackernoon1 year agoRoam ResearchUnderstanding Concentrability in Direct Nash Optimization | HackerNoon
