mlsanityData to 14 Oct 2026

Frontend Diffusion: Empowering Self-Representation of Junior Researchers and Designers Through Multi-agent System

arXiv 2502.03788 ↗First posted 6 Feb 2025cs.HCcited by 2

On the map: LLM reasoning → Reasoning for agents, planning and code

Abstract (arXiv)

With the continuous development of generative AI's logical reasoning abilities, AI's growing code-generation potential poses challenges for both technical and creative professionals. But how can these advances be directed toward empowering junior researchers and designers who often require additional help to build and express their professional and personal identities? We introduce Frontend Diffusion, a multi-agent coding system transforming user-drawn layouts and textual prompts into refined website code, thereby supporting self-representation goals. A user study with 13 junior researchers and designers shows AI as a human capability enhancer rather than a replacement, and highlights the importance of bidirectional human-AI alignment. We then discuss future work such as leveraging AI for career development and fostering bidirectional human-AI alignment of multi-agent systems.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. First posted on arXiv 6 Feb 2025.

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Citing papers per year: 2025: 1; 2026: 1.

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