Agentic Design Review System
This addresses the under-explored but pragmatic problem of holistic graphic design evaluation for designers and reviewers.
The paper tackles the problem of evaluating graphic designs by proposing AgenticDRS, a multi-agent system that collaboratively analyzes designs using a novel in-context exemplar selection and prompt expansion method, achieving state-of-the-art performance on the introduced DRS-BENCH benchmark.
Evaluating graphic designs involves assessing it from multiple facets like alignment, composition, aesthetics and color choices. Evaluating designs in a holistic way involves aggregating feedback from individual expert reviewers. Towards this, we propose an Agentic Design Review System (AgenticDRS), where multiple agents collaboratively analyze a design, orchestrated by a meta-agent. A novel in-context exemplar selection approach based on graph matching and a unique prompt expansion method plays central role towards making each agent design aware. Towards evaluating this framework, we propose DRS-BENCH benchmark. Thorough experimental evaluation against state-of-the-art baselines adapted to the problem setup, backed-up with critical ablation experiments brings out the efficacy of Agentic-DRS in evaluating graphic designs and generating actionable feedback. We hope that this work will attract attention to this pragmatic, yet under-explored research direction.