Harmanpreet Kaur

schoolUniversity of Minnesotabar_chart#1465 Global Rank

Total Papers

HCI Rank

#1465

Research Areas

Years Active

Recent Publications

An Expert Schema for Evaluating Large Language Model Errors in Scholarly Question-Answering Systems

Large Language Models (LLMs) are transforming scholarly tasks like search and summarization, but their reliability remains uncertain. Current evaluation metrics for testing LLM reliability are primarily automated approaches that prioritize efficiency and scalability, but lack contextual nuance and fail to reflect how…

CHI '26CorrespondingHuman-LLM Collaboration +3

PaperTrail: A Claim-Evidence Interface for Grounding Provenance in LLM-based Scholarly Q&A

Large language models (LLMs) are increasingly used in scholarly question-answering (QA) systems to help researchers synthesize vast amounts of literature. However, these systems often produce subtle errors (e.g., unsupported claims, errors of omission), and current provenance mechanisms like source citations are not g…

CHI '264th AuthorAI Ethics, Fairness & Accountability +3

Unraveling Entangled Feeds: Rethinking Social Media Design to Enhance User Well-being

Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design workshops with 21 participants diagnosed with mental illness about their interactions with social media platforms. We find that users develop ca…

CHI '265th+ AuthorHonorable MentionAI-Assisted Decision-Making & Automation +2

Opportunities and Barriers for AI Feedback on Meeting Inclusion in Socioorganizational Teams

Inclusion is important for meeting effectiveness, which is in turn central to organizational functioning. One way of improving inclusion in meetings is through feedback, but social dynamics make giving feedback difficult. We propose that AI agents can facilitate feedback exchange by being psychologically safer recipie…

CSCW '25CorrespondingCrowdsourcing & Peer Production

Wisdom of the Crowd, Without the Crowd: A Socratic LLM for Asynchronous Deliberation on Perspectivist Data

Data annotation underpins the success of modern AI, but the aggregation of crowd-collected datasets can harm the preservation of diverse perspectives in data. Difficult and ambiguous tasks cannot easily be collapsed into unitary labels. Prior work has shown that deliberation and discussion improve data quality and pre…

CHI '25CorrespondingGenerative AI (Text, Image, Music, Video) +2

Catalyst for Creativity or a Hollow Trend?: A Cross-Level Perspective on The Role of Generative AI in Design

Generative AI image creation tools have the potential to transform design education and practice, but raise critical concerns for creativity and ownership. We leverage the 2022 launch of tools like Midjourney and DALL.E as a point dividing design enthusiasts into pre- and post-tool learners. In this paper, we conduct…

CSCW '241st AuthorSession 1c: Tech Adoption: From Delivery Robots to Dumbphones

Interpretability Gone Bad: The Role of Bounded Rationality in How Practitioners Understand Machine Learning

While interpretability tools are intended to help people better understand machine learning (ML), we find that they can, in fact, impair understanding. This paper presents a pre-registered, controlled experiment showing that ML practitioners (N=119) spent 5x less time on task, and were 17% less accurate about the data…

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