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RefCraft: Benchmarking Visual-Reference-Conditioned Agentic Generation through Web Development

Paper recorded by Signals 4 on 2026-10-19 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20

Category: cs.AI · 人工智能 · first seen 2026-10-20

Abstract

Beyond basic tool use and coding skills, effectively incorporating visual references into agentic generation is equally essential for applying AI agents to real-world productivity tasks. We study this crucial capability through webpage development, a practical and readily evaluable setting in which existing benchmarks remain largely idealized: they typically focus on reconstructing visual targets

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#253 most recent of 960 cs.AI papers we have recorded · ↑ newer: Agent World Model in the Wild: Computer-Use Agent Environment Synthesi · ↓ older: AfriBED: a Speech Recognition Bias Evaluation Dataset for Low Resource
Cite this page: RefCraft: Benchmarking Visual-Reference-Conditioned Agentic Generation through Web Development: the #253 most recent of 960 cs.AI papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/refcraft-benchmarking-visual-reference-conditioned-agentic-generation-through-we.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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