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Alice Oh

ACL 2026×5CHI 2026评测与基准社会与人本对齐与偏好推理安全
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0 一作 · 6 篇 · ACL 2026 / CHI 2026

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2026 顶会论文

6
作者位次 #7/8ACL 2026Poster· Natural Language Processing

Are they lovers or friends? Evaluating LLM s’ Social Reasoning in E nglish and K orean Dialogues

Eunsu Kim · Junyeong Park · Juhyun Oh · Kiwoong Park · Seyoung Song · A. Seza Doğruöz · Alice Oh · Najoung Kim

摘要

As LLMs are increasingly deployed in real-world interactions, their social reasoning in interpersonal communication becomes critical. To explore their capabilities, we introduce SCRIPTS, a 1.1k-dialogue dataset in English and Korean, sourced from movie scripts and propose a social reasoning task...

推理社会与人本评测与基准OpenReview 项目页
作者位次 #8/9ACL 2026Poster· Natural Language Processing

Investigating Counterfactual Unfairness in LLM s towards Identities through Humor

Shubin Kim · Yejin Son · Junyeong Park · Keummin Ka · Seungbeen Lee · Jaeyoung Lee · Hyeju Jang · Alice Oh · Youngjae Yu

摘要

Humor holds up a mirror to social perception: what we find funny often reflects who we are and how we judge others. When language models engage with humor, their reactions expose the social assumptions they have internalized from training data. In this paper, we investigate counterfactual unfairn...

社会与人本对齐与偏好安全OpenReview 项目页
作者位次 #4/4ACL 2026Poster· Natural Language Processing

OLA : Output Language Alignment in Code-Switched LLM Interactions

Juhyun Oh · Haneul Yoo · Faiz Ghifari Haznitrama · Alice Oh

摘要

Code-switching, alternating between languages within a conversation, is natural for multilingual users, yet poses fundamental challenges for large language models (LLMs). When a user code-switches in their prompt to an LLM, they typically do not specify the expected language of the LLM response,...

推理对齐与偏好评测与基准OpenReview 项目页
作者位次 #7/7ACL 2026Poster· ACL Industry Track

L o C ar: Localization-Aware Evaluation of In-Vehicle Assistants through Fine-Grained Sociolinguistic Control

Seogyeong Jeong · Kiwoong Park · Seyoung Song · Eunsu Kim · Ken E Friedl · Jaeho Kim · Alice Oh

摘要

While Large Language Models (LLMs) are increasingly integrated into in-vehicle conversational systems, identifying the optimal model remains challenging due to the lack of domain-specific evaluation standards tailored to real-world deployment requirements. In this paper, we propose a novel evalua...

安全多模态评测与基准OpenReview 项目页
作者位次 #7/7ACL 2026Findings· Findings of ACL

R ole C onflict B ench: A Benchmark of Role Conflict Scenarios for Evaluating LLM s’ Contextual Sensitivity

Jisu Shin · Hoyun Song · Juhyun Oh · Changgeon Ko · Eunsu Kim · Chani Jung · Alice Oh

摘要

People often encounter role conflicts—social dilemmas where the expectations of multiple roles clash and cannot be simultaneously fulfilled. As large language models (LLMs) increasingly navigate these social dynamics, a critical research question emerges. When faced with such dilemmas, do LLMs pr...

评测与基准对齐与偏好数据与预训练OpenReview 项目页

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