activity
20242026
most citedAudienceView: AI-Assisted Interpretation of Audience Feedback in Journalism

3 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

Can We Trust Item Response Theory for AI Evaluation?

Han Jiang, Sunbeom Kwon, Jinwen Luo +2

AI benchmarks increasingly leverage item-level statistical models, particularly item response theory (IRT), to estimate capabilities, rank systems, select informative examples, and…

cs.AI2026★ 1 cited

AI Evaluation Should Require Standardized Item-Level Data Releases

Han Jiang, Susu Zhang, Dongyao Zhu +6

This position paper argues that standardized item-level benchmark data should become the default infrastructure for AI evaluation. Current evaluations suffer from underspecified it…

cs.AI2026★ 1 cited

Generative AI Assisted Workflows in Architectural Conceptual Design: Performance, Creative Self-Efficacy, and Cognitive Load

Han Jiang, Yao Xiao, Rachel Hurley +1

Generative AI (GenAI) is increasingly adopted in design education, yet evaluating its educational value through final outcomes provides an incomplete picture. This study compares t…

cs.HC2025

Human-AI Narrative Synthesis to Foster Shared Understanding in Civic Decision-Making

Cassandra Overney, Hang Jiang, Urooj Haider +6

Community engagement processes in representative political contexts, like school districts, generate massive volumes of feedback that overwhelm traditional synthesis methods, creat…

cs.AI2025

The Incomplete Bridge: How AI Research (Mis)Engages with Psychology

Han Jiang, Pengda Wang, Xiaoyuan Yi +2

Social sciences have accumulated a rich body of theories and methodologies for investigating the human mind and behaviors, while offering valuable insights into the design and unde…

cs.CL2025

Automatic Detection of Research Values from Scientific Abstracts Across Computer Science Subfields

Hang Jiang, Tal August, Luca Soldaini +2

The field of Computer science (CS) has rapidly evolved over the past few decades, providing computational tools and methodologies to various fields and forming new interdisciplinar…

cs.HC2024★ 3 cited

AudienceView: AI-Assisted Interpretation of Audience Feedback in Journalism

William Brannon, Doug Beeferman, Hang Jiang +2

Understanding and making use of audience feedback is important but difficult for journalists, who now face an impractically large volume of audience comments online. We introduce A…

cs.HC2024★ 1 cited

Bridging Dictionary: AI-Generated Dictionary of Partisan Language Use

Hang Jiang, Doug Beeferman, William Brannon +2

Words often carry different meanings for people from diverse backgrounds. Today's era of social polarization demands that we choose words carefully to prevent miscommunication, esp…