2 papers
cs.AI2026
MemWM: Memory-Augmented Text-Based World Model
Yujun Wang, Tao Zhang, Jinhe Bi +9
World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent next-state predictions can sti…
cs.CL2025
Improving Neural Question Generation using World Knowledge
Deepak Gupta, Kaheer Suleman, Mahmoud Adada +2
In this paper, we propose a method for incorporating world knowledge (linked entities and fine-grained entity types) into a neural question generation model. This world knowledge h…