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Haoran Li

7 papers indexed

arxivcs.CV2026-07-22

Self Gradient Forcing: Native Long Video Extrapolation

Junhao Zhuang, Shiyi Zhang, Yuxuan Bian, Yaowei Li, Yawen Luo, Yijun Liu, et al.

Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-truth video contexts. This reduces exposure bias, but the historical key-value cache is still used by f…

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arxivcs.AI2026-07-15

A Self-Evolving Agent for Longitudinal Personal Health Management

Haoran Li, Jiebi Deng, Tong Jin, Jinghong Han, Yuxin Wang, Zexin Wang, et al.

Personal health management unfolds over repeated encounters, yet most health AI systems treat each request in isolation. We developed HealthClaw, an open-source agent architecture that updates support as a person's routines, preferences, measurements and risks change. It separate…

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arxivcs.AI2026-07-14

Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions

Huihao Jing, Wenbin Hu, Shaojin Chen, Haochen Shi, Sirui Zhang, Hanyu Yang, et al.

The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequently, safety is no longer only about input--output content alignment. It also concerns system behavior and real-world execution out…

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arxivcs.RO2026-07-04

Look Before You Leap: Distilling Tree Search into Action Evaluation for Frozen VLA Models

Xinyi Xie, Zican Hu, Zhanyu Liu, Yicheng Dong, Wenhao Wu, Zhenhong Sun, et al.

Vision-Language-Action (VLA) models acquire broad embodied capabilities through large-scale pretraining, yet their generalization remains far more fragile than that of LLMs and VLMs. The prevailing remedy, post-training via supervised fine-tuning or reinforcement learning, improv…

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arxivcs.RO2026-07-02

VT-WAM: Visual-Tactile World Action Model for Contact-Rich Manipulation

Shuai Tian, Yupeng Zheng, Yuhang Zheng, Songen Gu, Yujie Zang, Yuxing Qin, et al.

Contact-rich manipulation requires policies to react to local deformation, pressure, slip, and friction, yet these cues are temporally sparse and often invisible in visual observations. Existing visual-tactile policies usually feed tactile observations directly into action predic…

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arxivcs.RO2026-06-26

Building a Scalable, Reproducible, Evaluatable, and Closed-Loop Simulation Environment Foundation for Embodied Intelligence

Junwu Xiong, Yongjian Guo, Mingxi Luo, Ning Qiao, Lei Kang, Song Wang, et al.

This paper presents a cloud-native simulation infrastructure framework for embodied intelligence that supports large-scale training, standardized evaluation, and simulation-based data collection. The framework unifies simulation environment generation, task execution, trajectory…

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