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

Berk Atıl

ACL 2026×2社会与人本多模态对齐与偏好评测与基准数据与预训练
新星分新星
60
一作贡献30
核心/参与5
方向广度10
合作网络6
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
作者位次 #6/9ACL 2026Findings· Findings of ACL

Self-Explaining Hate Speech Detection with Moral Rationales

Francielle Vargas · Jackson Trager · Diego Alves · Matteo Guida · Surendrabikram Thapa · Berk Atıl · Daryna Dementieva · Andrew J Smart · Ameeta Agrawal

摘要

Existing hate speech detection models are often opaque and rely on surface-level lexical cues, which makes them vulnerable to spurious correlations and limits robustness, interpretability and cultural contextualization. We propose Supervised Moral Rationale Attention (SMRA), the first self-explai...

社会与人本多模态对齐与偏好OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

♪ Something Just Like TR u ST ♪ *: Toxicity Recognition of Span and Target

Berk Atıl · Namrata Sureddy · Rebecca J. Passonneau

摘要

Toxic language includes content that is offensive, abusive, or that promotes harm. Progress in preventing toxic output from large language models (LLMs) is hampered by inconsistent definitions of toxicity. We introduce TRuST, a large-scale dataset that unifies and expands prior resources through...

评测与基准数据与预训练社会与人本OpenReview 项目页

常见合作者