Researchers propose QueryFormer, a unified architecture for post-click conversion rate prediction that bridges non-sequential multi-field features and behavioral sequences. The architecture uses a stackable unified field-sequence block with cross-attention and achieves state-of-the-art results on the KDD Cup 2026 Tencent UniRec Challenge. This development is relevant to people building or operating AI agents as it presents a new architecture for improving predictive modeling.