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

Hao Liu

SIGIR 2026×2多模态推理对齐与偏好安全可解释性
新星分新星
69
一作贡献40
核心/参与9
方向广度10
合作网络6
1 一作 · 2 篇 · SIGIR 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

2
作者位次 #3/5SIGIR 2026Oral· Information Retrieval (TOIS)

Cross-modal Representation Shift Refinement for Point-supervised Video Moment Retrieval

Kun Wang · an Jiaotong University) · Hao Liu · Jiang Shao · an Jiaotong University)

摘要

Video Moment Retrieval (VMR) aims to retrieve temporal moments in videos that align with natural language queries, a task requiring cross-modal reasoning between video and text. Among various supervision paradigms, point-supervised VMR has emerged as a practical solution, leveraging single-frame...

多模态推理对齐与偏好OpenReview
一作SIGIR 2026Oral· Information Retrieval (Full)

From Interference to Stability: Adversarial Reliability Correction for Video Moment Retrieval with Relevance Feedback

Hao Liu · an Jiaotong University) · Kun Wang · Junchao Wang · Ruping Cao · Yutao Yao · Zilu Cai

摘要

Video Moment Retrieval (VMR) aims to retrieve target video moments that correspond to natural language queries. Most existing methods rely on a positive-only assumption that the queried moment always exists within the video, which limits their reliability in practical scenarios. Departing from th...

多模态安全可解释性OpenReview

常见合作者