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Jun Luo

AAAI 2026×3ACL 2026INFOCOM 2026NeurIPS 2026多模态对齐与偏好安全推理效率与系统
新星分资深
25
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核心/参与4
方向广度19
合作网络6
0 一作 · 6 篇 · AAAI 2026 / ACL 2026 / INFOCOM 2026 / NeurIPS 2026

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2026 顶会论文

6
作者位次 #3/3ACL 2026Findings· Findings of ACL

To Intervene or Not: Guiding Inference-time Alignment with Probabilistic Model Blending

Jin Gan · Xin Li · Jun Luo

摘要

The wide deployment of LLMs has made model alignment necessary to make newly trained models safely and effectively respond to user instructions. Among different methods, inference-time alignment is often cheaper as it intervenes (i.e., offers guidances) only during output generation. Existing pro...

效率与系统对齐与偏好评测与基准OpenReview 项目页
作者位次 #4/4INFOCOM 2026Oral· Computer Communications & Networking

CloakFi: Metasurface-Enabled Privacy Protection for Wi-Fi Integrated Sensing and Communication

Yinghui He · Long Fan · Xin Li · Jun Luo

作者位次 #3/3AAAI 2026Poster· Artificial Intelligence

Where to Start Alignment? Diffusion Large Language Model May Demand a Distinct Position

Zhixin Xie · Xurui Song · Jun Luo

对齐与偏好OpenReview
作者位次 #4/4AAAI 2026Poster· Artificial Intelligence

Cheating Stereo Matching in Full-Scale: Physical Adversarial Attack Against Binocular Depth Estimation in Autonomous Driving

Kangqiao Zhao · Shuo Huai · Xurui Song · Jun Luo

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