2 citations · 2 across the 13 of their papers we have counts for
15 papers
Intergroup Bias Predicts Expressions of Social Judgment and Empathy in the r/AmITheAsshole Reddit Community
Yu Hou, Hal Daumé, Rachel Rudinger
People share and understand others' experiences differently based on their social identities; often, people empathize more when the other person belongs to their ingroup compared t…
The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations
Sandra C. Sandoval, Navita Goyal, Rashawn Ray +3
Against the backdrop of violence in police interactions with the U.S. public, we explore how deferentially police officers speak to virtual characters depicted as Black adult males…
On the Role of Citations in Preference Data
Yu Hou, Hal Daumé, Rachel Rudinger +1
Many NLP tasks require systems to provide attribution in their outputs--i.e. citations to grounding sources. Attribution serves as a bulwark against model hallucination and as a me…
Balancing Safety and Helpfulness in Healthcare AI Assistants through Iterative Preference Alignment
Huy Nghiem, Swetasudha Panda, Devashish Khatwani +3
Large Language Models (LLMs) are increasingly used in healthcare, yet ensuring their safety and trustworthiness remains a barrier to deployment. Conversational medical assistants m…
'Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ?
Huy Nghiem, Phuong-Anh Nguyen-Le, John Prindle +2
Large Language Models (LLMs) are increasingly involved in high-stakes domains, yet how they reason about socially sensitive decisions remains underexplored. We present a large-scal…
SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models
Huy Nghiem, Advik Sachdeva, Hal Daumé
WARNING: This paper contains examples of offensive materials. To address the proliferation of toxic content on social media, we introduce SMARTER, we introduce SMARTER, a data-effi…
Beyond Blanket Masking: Examining Granularity for Privacy Protection in Images Captured by Blind and Low Vision Users
Jeffri Murrugarra-LLerena, Haoran Niu, K. Suzanne Barber +3
As visual assistant systems powered by visual language models (VLMs) become more prevalent, concerns over user privacy have grown, particularly for blind and low vision users who m…
An Interdisciplinary Approach to Human-Centered Machine Translation
Marine Carpuat, Omri Asscher, Kalika Bali +17
Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between sy…
How May U.S. Courts Scrutinize Their Recidivism Risk Assessment Tools? Contextualizing AI Fairness Criteria on a Judicial Scrutiny-based Framework
Tin Nguyen, Jiannan Xu, Phuong-Anh Nguyen-Le +4
The AI/HCI and legal communities have developed largely independent conceptualizations of fairness. This conceptual difference hinders the potential incorporation of technical fair…
Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metrics
Tin Trung Nguyen, Jiannan Xu, Zora Che +6
Although popularized AI fairness metrics, e.g., demographic parity, have uncovered bias in AI-assisted decision-making outcomes, they do not consider how much effort one has spent…
A Necessary Step toward Faithfulness: Measuring and Improving Consistency in Free-Text Explanations
Lingjun Zhao, Hal Daumé
Faithful free-text explanations are important to ensure transparency in high-stakes AI decision-making contexts, but they are challenging to generate by language models and assess…
Which Demographic Features Are Relevant for Individual Fairness Evaluation of U.S. Recidivism Risk Assessment Tools?
Tin Trung Nguyen, Jiannan Xu, Phuong-Anh Nguyen-Le +4
Despite its constitutional relevance, the technical ``individual fairness'' criterion has not been operationalized in U.S. state or federal statutes/regulations. We conduct a human…
Language Models Predict Empathy Gaps Between Social In-groups and Out-groups
Yu Hou, Hal Daumé, Rachel Rudinger
Studies of human psychology have demonstrated that people are more motivated to extend empathy to in-group members than out-group members (Cikara et al., 2011). In this study, we i…
Can Hallucination Correction Improve Video-Language Alignment?
Lingjun Zhao, Mingyang Xie, Paola Cascante-Bonilla +2
Large Vision-Language Models often generate hallucinated content that is not grounded in its visual inputs. While prior work focuses on mitigating hallucinations, we instead explor…
My LLM might Mimic AAE -- But When Should it?
Sandra C. Sandoval, Christabel Acquaye, Kwesi Cobbina +2
We examine the representation of African American English (AAE) in large language models (LLMs), exploring (a) the perceptions Black Americans have of how effective these technolog…