activity
20232026
most citedSwitchGPT: Adapting Large Language Models for Non-Text Outputs

3 citations · 3 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2026

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…

cs.RO2026

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…

cs.SE2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

ModaVerse: Efficiently Transforming Modalities with LLMs

Xinyu Wang, Bohan Zhuang, Qi Wu

Humans possess the capability to comprehend diverse modalities and seamlessly transfer information between them. In this work, we introduce ModaVerse, a Multi-modal Large Language…

cs.CV2023★ 3 cited

SwitchGPT: Adapting Large Language Models for Non-Text Outputs

Xinyu Wang, Bohan Zhuang, Qi Wu

Large Language Models (LLMs), primarily trained on text-based datasets, exhibit exceptional proficiencies in understanding and executing complex linguistic instructions via text ou…