OmniAlpha is a unified multi-task RL framework that uses an alpha-aware VAE, sequence-to-sequence Diffusion Transformer, and layer-aware rewards to improve transparency-aware generation across five task categories.
Gpt-4 technical report, 2024
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XComp reaches extreme video compression (one token per selective frame) via learnable progressive token compression and question-conditioned frame selection, lifting LVBench accuracy from 42.9 percent to 46.2 percent after tuning on 2.5 percent of standard data.
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OmniAlpha: Aligning Transparency-Aware Generation via Multi-Task Unified Reinforcement Learning
OmniAlpha is a unified multi-task RL framework that uses an alpha-aware VAE, sequence-to-sequence Diffusion Transformer, and layer-aware rewards to improve transparency-aware generation across five task categories.
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One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding
XComp reaches extreme video compression (one token per selective frame) via learnable progressive token compression and question-conditioned frame selection, lifting LVBench accuracy from 42.9 percent to 46.2 percent after tuning on 2.5 percent of standard data.