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

Hongyao Yu

KDD 2026×3ACL 2026×2检索与知识安全可解释性评测与基准数据与预训练
新星分新星
82
一作贡献40
核心/参与28
方向广度13
合作网络12
1 一作 · 5 篇 · KDD 2026 / ACL 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

5
作者位次 #3/8ACL 2026Poster· Natural Language Processing

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models

Hao Fang · Xiaohang Sui · Hongyao Yu · Kuofeng Gao · Jiawei Kong · Sijin Yu · Bin Chen · Shu-Tao Xia

摘要

Diffusion models (DMs) have recently exhibited impressive generation capability. However, their training generally requires huge computational resources and large-scale datasets. To solve these, recent studies empower DMs with Retrieval-Augmented Generation (RAG), yielding retrieval-augmented dif...

安全检索与知识可解释性OpenReview 项目页
作者位次 #5/8ACL 2026Findings· Findings of ACL

C - R e D : A Comprehensive C hinese Benchmark for AI -Generated Text Detection Derived from Real-World Prompts

Chenxi Qing · Junxi Wu · Zheng Liu · Yixiang Qiu · Hongyao Yu · Bin Chen · Hao Wu · Shu-Tao Xia

摘要

Recently, large language models (LLMs) are capable of generating highly fluent textual content. While they offer significant convenience to humans, they also introduce various risks, like phishing and academic dishonesty. Numerous research efforts have been dedicated to developing algorithms for...

评测与基准数据与预训练检索与知识OpenReview 项目页

常见合作者