16 citations · 52 across the 17 of their papers we have counts for
17 papers
Evaluating Large Language Models for Antisemitic Incident Classification
Karina Halevy, Julia Mendelsohn, Chan Young Park +2
Addressing hate and violence in society requires timely detection of hateful events from public reporting, but automated identification of hateful events remains underexplored. We…
PrefPalette: Personalized Preference Modeling with Latent Attributes
Shuyue Stella Li, Melanie Sclar, Hunter Lang +7
Personalizing AI systems requires understanding not just what users prefer, but the reasons that underlie those preferences - yet current preference models typically treat human ju…
ComPO: Community Preferences for Language Model Personalization
Sachin Kumar, Chan Young Park, Yulia Tsvetkov +2
Conventional algorithms for training language models (LMs) with human feedback rely on preferences that are assumed to account for an "average" user, disregarding subjectivity and…
Locating Information Gaps and Narrative Inconsistencies Across Languages: A Case Study of LGBT People Portrayals on Wikipedia
Farhan Samir, Chan Young Park, Anjalie Field +2
To explain social phenomena and identify systematic biases, much research in computational social science focuses on comparative text analyses. These studies often rely on coarse c…
ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions
Chan Young Park, Shuyue Stella Li, Hayoung Jung +4
This study introduces ValueScope, a framework leveraging language models to quantify social norms and values within online communities, grounded in social science perspectives on n…
Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration
Shangbin Feng, Taylor Sorensen, Yuhan Liu +4
While existing alignment paradigms have been integral in developing large language models (LLMs), LLMs often learn an averaged human preference and struggle to model diverse prefer…
CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge
Yu Ying Chiu, Liwei Jiang, Maria Antoniak +7
Frontier large language models (LLMs) are developed by researchers and practitioners with skewed cultural backgrounds and on datasets with skewed sources. However, LLMs' (lack of)…
Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
Sachin Kumar, Chan Young Park, Yulia Tsvetkov
Language model (LM) prompting--a popular paradigm for solving NLP tasks--has been shown to be susceptible to miscalibration and brittleness to slight prompt variations, caused by i…
P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Models
Yuhan Liu, Shangbin Feng, Xiaochuang Han +4
In this work, we take a first step towards designing summarization systems that are faithful to the author's intent, not only the semantic content of the article. Focusing on a cas…
TalkUp: Paving the Way for Understanding Empowering Language
Lucille Njoo, Chan Young Park, Octavia Stappart +3
Empowering language is important in many real-world contexts, from education to workplace dynamics to healthcare. Though language technologies are growing more prevalent in these c…
Analyzing Norm Violations in Live-Stream Chat
Jihyung Moon, Dong-Ho Lee, Hyundong Cho +6
Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and no…
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
Shangbin Feng, Chan Young Park, Yuhan Liu +1
Language models (LMs) are pretrained on diverse data sources, including news, discussion forums, books, and online encyclopedias. A significant portion of this data includes opinio…
Challenges and Opportunities in Information Manipulation Detection: An Examination of Wartime Russian Media
Chan Young Park, Julia Mendelsohn, Anjalie Field +1
NLP research on public opinion manipulation campaigns has primarily focused on detecting overt strategies such as fake news and disinformation. However, information manipulation in…
Controlled Analyses of Social Biases in Wikipedia Bios
Anjalie Field, Chan Young Park, Kevin Z. Lin +1
Social biases on Wikipedia, a widely-read global platform, could greatly influence public opinion. While prior research has examined man/woman gender bias in biography articles, po…
Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia
Chan Young Park, Xinru Yan, Anjalie Field +1
Specific lexical choices in narrative text reflect both the writer's attitudes towards people in the narrative and influence the audience's reactions. Prior work has examined descr…
NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer
Hwijeen Ahn, Jimin Sun, Chan Young Park +1
This paper describes our approach to the task of identifying offensive languages in a multilingual setting. We investigate two data augmentation strategies: using additional semi-s…
Cross-Cultural Similarity Features for Cross-Lingual Transfer Learning of Pragmatically Motivated Tasks
Jimin Sun, Hwijeen Ahn, Chan Young Park +2
Much work in cross-lingual transfer learning explored how to select better transfer languages for multilingual tasks, primarily focusing on typological and genealogical similaritie…