6 papers
Demystifying Agent Skills: Why They Work-Until They Don't
Zhiyuan Jiang, Fangrui Huang, Hanwen Xing +6
Skills have emerged as a practical and effective approach for enhancing LLM agents at inference time through structured packages of knowledge. However, existing evaluations largely…
LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models
Zhiyuan Jiang, Weihao Hong, Xinlei Guan +8
Vision-Language Models (VLMs) are increasingly deployed in settings where reliable visual grounding carries operational consequences, yet their behavior under progressively coerciv…
Tone Matters: The Impact of Linguistic Tone on Hallucination in VLMs
Weihao Hong, Zhiyuan Jiang, Bingyu Shen +4
Vision-Language Models (VLMs) are increasingly used in safety-critical applications that require reliable visual grounding. However, these models often hallucinate details that are…
Wow, wo, val! A Comprehensive Embodied World Model Evaluation Turing Test
Chun-Kai Fan, Xiaowei Chi, Xiaozhu Ju +18
As world models gain momentum in Embodied AI, an increasing number of works explore using video foundation models as predictive world models for downstream embodied tasks like 3D p…
Zoom in, Click out: Unlocking and Evaluating the Potential of Zooming for GUI Grounding
Zhiyuan Jiang, Shenghao Xie, Wenyi Li +8
Grounding is a fundamental capability for building graphical user interface (GUI) agents. Although existing approaches rely on large-scale bounding box supervision, they still face…
WoW: Towards a World omniscient World model Through Embodied Interaction
Xiaowei Chi, Peidong Jia, Chun-Kai Fan +33
Humans develop an understanding of intuitive physics through active interaction with the world. This approach is in stark contrast to current video models, such as Sora, which rely…