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

Yuhua Li

CVPR 2026×6ACL 2026×2AAAI 2026ICLR 2026多模态效率与系统可解释性社会与人本理论与学习动力学
新星分贡献者
77
一作贡献0
核心/参与52
方向广度19
合作网络9
0 一作 · 10 篇 · CVPR 2026 / ACL 2026 / AAAI 2026 / ICLR 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

10
作者位次 #2/5CVPR 2026Poster· Computer Vision & Pattern Recognition

Is Bin Generation Indispensable? A Bin-Generation-Free Dataset Quantization via Semantic Perspective

Maijie Deng · Yuhua Li · Yixiong Zou · Yao Wu · Chenru Ma

多模态效率与系统数据与预训练OpenReview 项目页
作者位次 #3/4CVPR 2026Poster· Computer Vision & Pattern Recognition

Interpretable Cross-Domain Few-Shot Learning with Rectified Target-Domain Local Alignment

Yaze Zhao · Yixiong Zou · Yuhua Li · Ruixuan Li

对齐与偏好可解释性多模态OpenReview 项目页
作者位次 #5/7ACL 2026Poster· Natural Language Processing

UMPIRE : Unveiling LLM -generated Posts via Redundant Expressions

xiaoquan Yi · Haixing Wu · Haozhao Wang · Yichen Li · Yuhua Li · Rui Zhang · Ruixuan Li

摘要

The proliferation of Large Language Models (LLMs) has saturated social media platforms with hyper-realistic posts, rendering traditional detection methods that rely on low-level artifacts or unimodal statistics increasingly ineffective. In this work, we identify a fundamental semantic distinction...

社会与人本可解释性多模态OpenReview 项目页
作者位次 #6/9ACL 2026Findings· Findings of ACL

E cho MLLM : Incentivizing Echocardiographic Video Understanding with Keyframe Grounding and Report Generation

Heyu Huang · Wanran Sun · Chi Chen · Bo Chen · Zonghao Guo · Yuhua Li · Ruixuan Li · Kunlun He · Maosong Sun

摘要

Echocardiography analysis demands a dual capability: rigorous quantitative keyframe localization for evidence verification and comprehensive qualitative synthesis for diagnostic reporting. However, current Multi-Modal Large Language Models (MLLMs) struggle to meet these clinical requirements due...

多模态推理强化学习与后训练OpenReview 项目页

常见合作者