Rule-Compliant Visual Spatial Planning for Multimodal Large Language Models
[Sztuczna inteligencja] Autorzy: Yu Chen, Ting Lei, Yaoyi Li i 3 więcej
Multimodal large language models (MLLMs) combine linguistic reasoning with visual perception, yet their ability to perform visual spatial planning under explicit or previously unseen rule constraints remains underexplored. This setting requires models to jointly understand spatial layouts, interpret natural-language rules, and plan valid actions accordingly. To address this gap, we introduce RuleMaze, a controllable benchmark in which MLLMs must navigate mazes while obeying natural-language rules of varying complexity. RuleMaze isolates rule-compliant spatial planning by requiring accurate perception, rule interpretation, and constrained action planning. To enable scalable and systematic rule construction, we propose Language-Logic-Function Hybridization, which automatically generates natural-language rules and translates them into logical representations and executable validators, elim…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja