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Yuan Xu

6 papers indexed

arxivcs.CV2026-07-20

Style over Substance: A Shortcut Audit of Emotion-Description Preference Evaluation

Jiabing Yang, Yixiang Chen, Yuan Xu, Qisen Ma, Tao Yu, Peiyan Li, et al.

Preference over model-generated emotion descriptions is emerging as a standard evaluation metric for multimodal emotion understanding, exemplified by the MER2026 MER-Prefer track on EmoPrefer. Such benchmarks assume that predicting the preferred description requires grounded cros…

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arxivcs.ROcs.AIcs.CV2026-07-15

Semantic Anchoring for Robotic Action Representations

Yuan Xu, Youheng Shi, Chengyang Li, Wentao Zhu, Yizhou Wang

Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot demonstrations degrades this structure and undermines generalization. A fundamental question therefore arises: what constitutes a goo…

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arxivcs.ROcs.CV2026-07-14

FlowWAM: Optical Flow as a Unified Action Representation for World Action Models

Yixiang Chen, Peiyan Li, Yuan Xu, Qisen Ma, Jiabing Yang, Kai Wang, et al.

World Action Models (WAMs) are able to leverage pretrained video generators for both world modeling and action prediction. However, directly leveraging such video generators for control raises a new challenge: how to represent actions in a suitable form that aligns with pretraine…

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arxivcs.ROcs.CV2026-06-26

DIM-WAM: World-Action Modeling with Diverse Historical Event Memory

Kai Wang, Zhaopeng Gu, Yixiang Chen, Yuan Xu, Qisen Ma, Jiabing Yang, et al.

World-action models have shown promising robot-manipulation performance by jointly predicting future visual states and actions. However, existing methods mainly rely on short-term history and short-horizon future prediction, which is insufficient for long-horizon tasks whose corr…

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arxivcs.ROcs.AI2026-06-25

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

Wen Ye, Peiyan Li, Tingyu Yuan, Yuan Xu, Xiangnan Wu, Chaoyang Zhao, et al.

Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reasoning can effectively improve the performance of the policy, but its scaling mechanism has seldom been studied; (2) historical info…

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crossrefMicromachines2023-11-12Cited by 1

Extreme Learning Machine/Finite Impulse Response Filter and Vision Data-Assisted Inertial Navigation System-Based Human Motion Capture

Yuan Xu, Rui Gao, Ahong Yang, Kun Liang, Zhongwei Shi, Mingxu Sun, et al.

To obtain accurate position information, herein, a one-assistant method involving the fusion of extreme learning machine (ELM)/finite impulse response (FIR) filters and vision data is proposed for inertial navigation system (INS)-based human motion capture. In the proposed method…

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