5 papers
Do World Action Models Generalize Better than VLAs? A Robustness Study
Zhanguang Zhang, Zhiyuan Li, Behnam Rahmati +11
Robot action planning in the real world is challenging as it requires not only understanding the current state of the environment but also predicting how it will evolve in response…
TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs
Ziyi Wang, Chen Zhang, Wenjun Peng +2
Explainability for Large Language Model (LLM) agents is especially challenging in interactive, partially observable settings, where decisions depend on evolving beliefs and other a…
ProxyWar: Dynamic Assessment of LLM Code Generation in Game Arenas
Wenjun Peng, Xinyu Wang, Qi Wu
Large language models (LLMs) have revolutionized automated code generation, yet the evaluation of their real-world effectiveness remains limited by static benchmarks and simplistic…
NavBench: Probing Multimodal Large Language Models for Embodied Navigation
Yanyuan Qiao, Haodong Hong, Wenqi Lyu +5
Multimodal Large Language Models (MLLMs) have demonstrated strong generalization in vision-language tasks, yet their ability to understand and act within embodied environments rema…
Are Large Vision Language Models Good Game Players?
Xinyu Wang, Bohan Zhuang, Qi Wu
Large Vision Language Models (LVLMs) have demonstrated remarkable abilities in understanding and reasoning about both visual and textual information. However, existing evaluation m…