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reward

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Promptable, training-free, plug-and-play differentiable rewards from Vision-Language Models (VLMs) to guide image generation. Specify what/how to reward via prompts; backprop through the VLM with no fine-tuning. Includes anti-periodic loss functions that suppress the 16x16 pattern from image-token patching for cleaner textures.

  • Updated Aug 20, 2025
  • Python

Event-driven backtesting with realistic stop/target exits — showing that exit methodology can matter as much as the signal itself, validated with cross-asset consistency, independence correction, and out-of-sample testing.

  • Updated Sep 7, 2026
  • Python

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