3 papers
cs.AI2026
CreativityBench: Evaluating Agent Creative Reasoning via Affordance-Based Tool Repurposing
Cheng Qian, Hyeonjeong Ha, Jiayu Liu +10
Recent advances in large language models have led to strong performance on reasoning and environment-interaction tasks, yet their ability for creative problem-solving remains under…
cs.AI2026
Current Agents Fail to Leverage World Model as Tool for Foresight
Cheng Qian, Emre Can Acikgoz, Bingxuan Li +8
Agents built on vision-language models increasingly face tasks that demand anticipating future states rather than relying on short-horizon reasoning. Generative world models offer…
cs.CL2025
EscapeBench: Towards Advancing Creative Intelligence of Language Model Agents
Cheng Qian, Peixuan Han, Qinyu Luo +9
Language model agents excel in long-session planning and reasoning, but existing benchmarks primarily focus on goal-oriented tasks with explicit objectives, neglecting creative ada…