arXiv Computer Vision By Yilong Guo, Hanqi Chen, Zixiao Ye, Guanzhong Wang, Chen Yu, Zeyu Chen

Rendering-in-the-Loop: An Execution-Driven Agent for Interactive Web Development

Read the original on arXiv Computer Vision →

RILA is an execution‑driven agent that integrates browser rendering into the generation loop for interactive web development. It uses an Action Interaction Verification module to replay reference interactions on generated pages, collecting execution‑aware observations, and an Execution‑aware Rendering Score to jointly assess interaction correctness and visual fidelity during iterative optimization. A data synthesis pipeline further augments training data, enabling RILA to significantly improve interaction and visual quality across foundation models, even outperforming larger one‑shot generators.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

arXiv Machine Learning
Jun 11

FronTalk: Benchmarking Front-End Development as Conversational Code Generation with Multi-Modal Feedback

arXiv:2601. 04203v2 Announce Type: replace-cross Abstract: We present FronTalk, a benchmark for front-end code generation that pioneers the study of a unique interaction dynamic: conversational code generation with multi-modal feedback.

By Xueqing Wu, Zihan Xue, Da Yin, Shuyan Zhou, Kai-Wei Chang, Nanyun Peng, Yeming Wen