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DSAQuant reveals that aligning quantization training with the stage-wise nature of video diffusion can drastically enhance visual fidelity in text-to-video generation.
LingBot-VA 2.0 achieves few-shot generalization in complex robot manipulation tasks, outperforming traditional video generative models.
GPTQ-style quantization can be significantly improved by directly aligning quantized layer outputs with the original full-precision model's output, rather than the compensated weights, and accounting for "compensation-aware error."
