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Xinyu Liu

8 papers indexed

arxivcs.ROcs.AI2026-07-23

VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

Jiabin Lou, Haopeng Wang, Yuanshuai Wang, Xinyu Liu, Xuxin Lv, Yuxin Guo, et al.

Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orientation, distance, and layout, that are not explicitly available from onboard sensing at deployment…

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arxivcs.CV2026-07-23

Do Pathology Vision-Language Models Truly See Pathology?

Chengyang Zhang, Wenchuan Zhang, Bo Li, Xinyu Liu, Jiaming Yang, Mengran Li, et al.

Pathology vision-language models (VLMs) have recently progressed rapidly and are commonly evaluated by answer accuracy on pathology VQA benchmarks. However, we dig into current evaluations and identify three overlooked issues: 1) Visual evidence is not always necessary. For insta…

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arxivcs.CV2026-07-16

ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu, Shihao Li, Weihong Lin, Xinlong Chen, Yang Shi, Yujin Han, et al.

Recent diffusion-based video generation models have made significant progress in multi-reference image-conditioned video editing. However, existing methods still struggle to coordinate information from multiple visual sources accurately. We identify a critical deficiency in exist…

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arxivcs.LGq-bio.QM2026-07-12

Scaffold splits hide structural-frontier failures in ADMET models

Jiacheng Zheng, Chang Guo, Zixuan Wang, Xinyu Liu

Molecular property models are commonly evaluated by holding out Bemis--Murcko scaffolds, yet a scaffold identifier is only one notion of chemical unfamiliarity. We introduce a label-free structural-frontier split that reserves the sparsest and most physicochemically remote scaffo…

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arxivcs.CV2026-07-11

Structured Evidence Selection for Weakly Supervised Video Anomaly Detection

Chenglizhao Chen, Tianxiang Nan, Wen Li, Xinyu Liu, Guisheng Zhang, Mengke Song, et al.

Weakly supervised video anomaly detection relies solely on video-level labels for training, making it difficult to accurately localize anomalous events in complex scenes. In real-world videos, anomalous behaviors exhibit large variations in appearance and temporal duration, while…

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arxivcs.RO2026-06-29

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation

Ying Yuan, Xinyu Liu, Sriram Krishna, David Held

Large-scale dexterous grasp datasets encode rich priors over hand-object interaction, but their use has largely been confined to grasp generation and pick-and-place manipulation. We study whether such data can instead support functional dexterity in articulated tool use, where a…

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arxivcs.RO2026-06-29

AERIS: Aerial-Edge Role-Driven Intelligence at Runtime via Orchestrated Language-Model Swarm

Jiabin Lou, Haopeng Wang, Xinyu Liu, Yu Zhang, Rongye Shi, Wenjun Wu

Integrating large language models into robotic systems holds promise for enhancing autonomy, yet practical deployment remains constrained by strict heartbeat-constrained scheduling and limited computational power. We propose AERIS: an edge deployment framework for aerial platform…

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