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cs.AI2026
GlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations
Nicholas Saban, Charvi Bannur, Mariya Vasileva +1
Text-based world models have recently shown potential to simulate complex RL environment state transitions for a diverse set of use cases. However, no standardized benchmark exists…
cs.AI2026
Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL
Darshan Deshpande
Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixed task and reward difficulties b…