paper.dinq.meAI 与前沿科学顶会 · 学术新星雷达
登录 DINQ
返回新星榜
KC

Kanzhi Cheng

ACL 2026×2NeurIPS 2026智能体与工具多模态评测与基准安全检索与知识
新星分贡献者
52
一作贡献0
核心/参与15
方向广度13
合作网络12
0 一作 · 3 篇 · ACL 2026 / NeurIPS 2026

获取完整研究档案

首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。

联系方式

实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。

2026 顶会论文

3
作者位次 #36/45NeurIPS 2026Poster

OS-Omni: A Cross-Platform Benchmark for Generalist Computer-Using Agents

Hui Shen · Yunta Hsieh · Jianing Ma · Ziyuan Liu · Qi Han · Xiuqi Xu · Yanheng shang · Chenqi Yin · Zesen Zhao · Boyuan Zheng · Jisen Li · Xiaoxia Wu · Ruoyan Zhang · Dongfu Jiang · Ruiyao Liu · Jing Xiong · He Xiao · Nan Zheng · Hangxiang Chen · Shengyang Tao · Deyang Luorong · Jingxuan Zhang · Chaofan Tao · Yuren Wang · Jiaqi Mo · Hei Ting Chan · Sicheng Chen · Kai Zhang · Mengkang Hu · Zhongwei Wan · Xin Wang · Chuanyang Zheng · Ziheng Zhang · Hengyuan Zhang · Zunhai Su · Kanzhi Cheng · Jiawei Lu · Yifan Zhang · Shen Yan · Ben Athiwaratkun · Qiushi Sun · Mi Zhang · Ping Luo · Wenhu Chen · Ngai Wong

智能体与工具评测与基准OpenReview
作者位次 #7/14ACL 2026Poster· Natural Language Processing

OS -Sentinel: Towards Safety-Enhanced Mobile GUI Agents via Hybrid Validation in Realistic Workflows

Qiushi Sun · Mukai Li · Zhoumianze Liu · Zhihui Xie · Fangzhi Xu · Zhangyue Yin · Kanzhi Cheng · Zehao Li · Zichen Ding · Qi Liu · Zhiyong Wu · Zhuosheng Zhang · Ben Kao · Lingpeng Kong

摘要

Computer-using agents powered by Vision-Language Models (VLMs) have demonstrated human-like capabilities in operating digital environments like mobile platforms. While these agents hold great promise for advancing digital automation, their potential for unsafe operations, such as system compromis...

智能体与工具安全多模态OpenReview 项目页
作者位次 #10/15ACL 2026Poster· Natural Language Processing

OS -Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agents

Bowen Yang · Kaiming Jin · Zhenyu Wu · Zhaoyang Liu · Qiushi Sun · Zehao Li · JingJing Xie · Zhoumianze Liu · Fangzhi Xu · Kanzhi Cheng · Yian Wang · Qingyun Li · Yu Qiao · Zun Wang · Zichen Ding

摘要

While Vision-Language Models (VLMs) have significantly advanced Computer-Using Agents (CUAs), current agentic frameworks struggle with robustness in novel domains and long-horizon workflows due to the absence of visual-aware tutorial retrieval and the lack of granular control over historical visu...

多模态检索与知识智能体与工具OpenReview 项目页

常见合作者