Prompt Engineering

在 DeepMind 的測試條件下，抽象草圖可能是影響模型物理推理準確率的因素之一。VIPE 透過自動將輸入圖像轉為寫實風格，讓 Veo 3.1 準確率從 41.3% 躍升至 59.3%。這在受測範圍內指出了一個方向：在花大錢增加算力之前，先搞清楚模型到底看到了什麼。

Under DeepMind’s test conditions, abstract sketches may be one factor affecting a model’s physical-reasoning accuracy. VIPE automatically converts input images into a photorealistic style, raising Veo 3.1 accuracy on VPCT from 41.3% to 59.3%, while Omni Flash rises from 56.3% to 67.5%. Within the tested scope, this points to a direction: before spending heavily on more compute, first clarify what the model is actually seeing.