Beyond Mode Collapse: Generating Diverse Synthetic Expert Conversations via Generative Flow Networks
This work shows that training GFlowNets to generate latent conversation structure using a Gaussian mixture density over key interaction features enables sampling expert strategies in proportion to their prevalence in the training data to provide a stronger training signal than competitive synthesis baselines.