The authors applied Adaptive Reward Routing to DiffusionNFT, a forward-process reinforcement-learning framework that directly supervises sampled diffusion or flow-matching timesteps.
Adaptive reward routing improves joint audio-video diffusion training
The method dynamically redirects learning signals across model components and adjusts competing reward weights while retaining user-defined priorities.
Chinese Tech
Songlin Yang · Xiaotong Zhao · Jiacheng Zhang · Zhe Wang · Toyota Li · Eric Liu · +2 more
MMLab@HKUST · The Hong Kong University of Science and Technology · Tencent Video · The University of Hong Kong
Research Digest··3 min read
Yang and colleagues treat reinforcement learning for joint audio-video generation as a changing credit-assignment problem: the model must determine both where each reward should update the network and how strongly that reward should count.
Why this paper
From Tencent Video and 3 others
In one line
Adaptive Reward Routing dynamically adapts update locations and reward weights, improving joint audio-video diffusion across multiple metrics.
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