7 papers
LIBERO-Pro2.0: A Benchmark for Evaluating the Robustness of Embodied Foundation Models
Xueyang Zhou, Yangming Xu, Qianjiang Li +10
LIBERO has emerged as a widely adopted benchmark for evaluating robotic manipulation policies. However, strong performance on LIBERO does not necessarily indicate robust embodied c…
EventLens: Event-Structure Reinforcement Learning for Video Understanding
Guowen Zhang, Boshen Xu, Zihao Yue +6
Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent. Th…
LocateAnything3D: Vision-Language 3D Detection with Chain-of-Sight
Yunze Man, Shihao Wang, Guowen Zhang +7
To act in the world, a model must name what it sees and know where it is in 3D. Today's vision-language models (VLMs) excel at open-ended 2D description and grounding, yet multi-ob…
LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
Xueyang Zhou, Yangming Xu, Guiyao Tie +5
LIBERO has emerged as a widely adopted benchmark for evaluating Vision-Language-Action (VLA) models; however, its current training and evaluation settings are problematic, often le…
BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization
Xueyang Zhou, Guiyao Tie, Guowen Zhang +3
Vision-Language-Action (VLA) models have advanced robotic control by enabling end-to-end decision-making directly from multimodal inputs. However, their tightly coupled architectur…
Exploring the Necessity of Reasoning in LLM-based Agent Scenarios
Xueyang Zhou, Guiyao Tie, Guowen Zhang +7
The rise of Large Reasoning Models (LRMs) signifies a paradigm shift toward advanced computational reasoning. Yet, this progress disrupts traditional agent frameworks, traditionall…
OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework
Wei Zhou, Hong Huang, Guowen Zhang +4
Large language models (LLMs) have excelled in various natural language processing tasks, but challenges in interpretability and trustworthiness persist, limiting their use in high-…