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

Tarek Mahmoud

ACL 2026×2数据与预训练可解释性强化学习与后训练社会与人本对齐与偏好
新星分新星
65
一作贡献30
核心/参与5
方向广度10
合作网络12
1 一作 · 2 篇 · 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

2
一作ACL 2026Poster· Natural Language Processing

Uncovering Temporal Framing in the News

Tarek Mahmoud · Veronika Solopova · Premtim Sahitaj · Ariana Sahitaj · Max Upravitelev · Mervat Abassy · Hana Fatima Shaikh · Neda Foroutan · Vera Schmitt · Preslav Nakov

摘要

Temporal language does more than place events on a timeline. In news discourse, references to the past, present, and future can function as rhetorical devices that shape interpretation and persuasion. Here, we study temporal framing , defined as the persuasive use of time-related language to stru...

数据与预训练可解释性强化学习与后训练OpenReview 项目页
作者位次 #14/26ACL 2026Poster· Natural Language Processing

Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI

Yuxia Wang · Rui Xing · Jonibek Mansurov · Giovanni Puccetti · Zhuohan Xie · Minh Ngoc Ta · Jiahui Geng · Jinyan Su · Mervat Abassy · Saadeldine Eletter · Kareem Elozeiri · Nurkhan Laiyk · Maiya Goloburda · Tarek Mahmoud · Raj Vardhan Tomar · Alexander Aziz · Ryuto Koike · Masahiro Kaneko · Artem Shelmanov · Ekaterina Artemova · Vladislav Mikhailov · Akim Tsvigun · Alham Fikri Aji · Nizar Habash · Iryna Gurevych · Preslav Nakov

摘要

Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random guessing. To verify the generalizability of this finding across languages and domains, we perform an extensive case...

社会与人本对齐与偏好数据与预训练OpenReview 项目页

常见合作者