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

Ling Chen

ACL 2026×5ICLR 2026×3AAAI 2026×2KDD 2026推理多模态安全社会与人本评测与基准
新星分资深
42
一作贡献0
核心/参与34
方向广度19
合作网络12
0 一作 · 11 篇 · ACL 2026 / ICLR 2026 / AAAI 2026 / KDD 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

11
作者位次 #4/4ICLR 2026Poster· Social Aspects / Trustworthy Machine Learning

Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection

Yongxin Deng · Zhen Fang · Sharon Li · Ling Chen

安全社会与人本OpenReview
作者位次 #4/6ICLR 2026Poster· General Machine Learning / Everything Else

Delving into Spectral Clustering with Vision-Language Representations

Bo Peng · Yuanwei Hu · Bo Liu · Ling Chen · Jie Lu · Zhen Fang

可解释性多模态OpenReview
作者位次 #6/7ACL 2026Poster· Natural Language Processing

MMCLIP : Cross-Modal Attention Masked Modelling for Medical Language-Image Pre-Training

Biao Wu · Yutong Xie · Zeyu Zhang · Vu Minh Hieu Phan · Qi Chen · Ling Chen · Qi Wu

摘要

Vision-and-language pretraining (VLP) in medicine leverages contrastive learning on image–text pairs, often enhanced with masked modeling. However, existing methods face two challenges: difficulty reconstructing key pathological features due to limited data, and reliance on either paired or image...

多模态数据与预训练推理OpenReview 项目页
作者位次 #3/3ACL 2026Poster· Natural Language Processing

Benchmarking Web Agent Safety under E -commerce Deceptive Interfaces

Zijing Shi · Meng Fang · Ling Chen

摘要

As autonomous web agents are increasingly deployed to perform real-world tasks, ensuring their safety has become a critical concern. In this work, we study web agent behavior under realistic deceptive interfaces in the e-commerce domain. We introduce WebDecept, a lightweight and configurable plug...

评测与基准智能体与工具安全OpenReview 项目页
作者位次 #4/4ACL 2026Findings· Findings of ACL

DOSE : Data Selection for Multi-Modal LLM s via Off-the-Shelf Models

Biao Wu · Yiwu Zhong · Meng Fang · Ling Chen

摘要

High-quality and diverse multimodal data are essential for improving vision–language models (VLMs), yet existing datasets often contain noisy, redundant, and poorly aligned samples. To address these problems, data filtering is commonly used to enhance the efficiency and performance of multimodal...

多模态数据与预训练推理OpenReview 项目页
作者位次 #9/11ACL 2026Findings· Findings of ACL

Infinity-Parser: Layout-Aware Reinforcement Learning with High-quality Document Parsing Dataset

Baode Wang · Biao Wu · Weizhen Li · Meng Fang · Zuming Huang · Jun Huang · Yanjie Liang · Haozhe WANG · Ling Chen · Wei Chu · Yuan Qi

摘要

Document parsing from scanned images into structured formats remains a significant challenge due to its complexly intertwined elements such as text paragraphs, figures, formulas, and tables. Existing supervised fine-tuning methods often struggle to generalize across diverse document types, leadin...

多模态强化学习与后训练评测与基准OpenReview 项目页
作者位次 #12/12ACL 2026Findings· Findings of ACL

You Never Know a Person, You Only Know Their Defenses: Detecting Levels of Psychological Defense Mechanisms in Supportive Conversations

Hongbin Na · Zimu Wang · Zhaoming Chen · Peilin Zhou · Yining Hua · Grace Ziqi Zhou · Haiyang Zhang · Tao Shen · Wei Wang · John Torous · Shaoxiong Ji · Ling Chen

摘要

Psychological defenses are strategies, often automatic, that people use to manage distress. Rigid use or overuse of defenses is negatively linked to mental health and shapes what speakers disclose and how they accept or resist help. However, defenses are complex and difficult to reliably measure,...

评测与基准社会与人本推理OpenReview 项目页
作者位次 #3/6AAAI 2026Poster· Artificial Intelligence

Vision-Language Reasoning for Geolocalization: A Reinforcement Learning Approach

Biao Wu · Meng Fang · Ling Chen · Ke Xu · Tao Cheng · Jun Wang

推理多模态强化学习与后训练OpenReview

常见合作者