Flow-GRPO is the first online RL method for flow matching models, raising GenEval accuracy from 63% to 95% and text-rendering accuracy from 59% to 92% with little reward hacking.
F5r-tts: Improving flow matching based text-to-speech with group relative policy optimization
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CosyVoice 3 achieves better content consistency, speaker similarity, and prosody naturalness in zero-shot multilingual speech synthesis by scaling data to one million hours, model size to 1.5 billion parameters, and introducing a supervised multi-task speech tokenizer plus a differentiable reward模型.
TIGFlow-GRPO uses a Trajectory-Interaction-Graph in conditional flow matching plus Flow-GRPO optimization to produce more accurate, socially compliant, and physically feasible trajectory forecasts on ETH/UCY and SDD datasets.
citing papers explorer
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Flow-GRPO: Training Flow Matching Models via Online RL
Flow-GRPO is the first online RL method for flow matching models, raising GenEval accuracy from 63% to 95% and text-rendering accuracy from 59% to 92% with little reward hacking.
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CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
CosyVoice 3 achieves better content consistency, speaker similarity, and prosody naturalness in zero-shot multilingual speech synthesis by scaling data to one million hours, model size to 1.5 billion parameters, and introducing a supervised multi-task speech tokenizer plus a differentiable reward模型.
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TIGFlow-GRPO: Trajectory Forecasting via Interaction-Aware Flow Matching and Reward-Guided Optimization
TIGFlow-GRPO uses a Trajectory-Interaction-Graph in conditional flow matching plus Flow-GRPO optimization to produce more accurate, socially compliant, and physically feasible trajectory forecasts on ETH/UCY and SDD datasets.