most citedEpistemic Alignment: A Mediating Framework for User-LLM Knowledge Delivery

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Bridging Human Interpretation and Machine Representation: A Landscape of Qualitative Data Analysis in the LLM Era

Xinyu Pi, Qisen Yang, Chuong Nguyen +1

LLMs are increasingly used to support qualitative research, yet existing systems produce outputs that vary widely--from trace-faithful summaries to theory-mediated explanations and…

cs.HC2025

Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI For Reciprocal Human-AI Futures

Hua Shen, Tiffany Knearem, Divy Thakkar +9

The rapid integration of generative AI into everyday life underscores the need to move beyond unidirectional alignment models that only adapt AI to human values. This workshop focu…

cs.HC2025

Beyond One-Way Influence: Bidirectional Opinion Dynamics in Multi-Turn Human-LLM Interactions

Yuyang Jiang, Longjie Guo, Yuchen Wu +3

Large language model (LLM)-powered chatbots are increasingly used for opinion exploration. Prior research examined how LLMs alter user views, yet little work extended beyond one-wa…

cs.HC20251 cited

Epistemic Alignment: A Mediating Framework for User-LLM Knowledge Delivery

Nicholas Clark, Hua Shen, Bill Howe +1

LLMs increasingly serve as tools for knowledge acquisition, yet users cannot effectively specify how they want information presented. When users request that LLMs "cite reputable s…

cs.HC2025

Mind the Value-Action Gap: Do LLMs Act in Alignment with Their Values?

Hua Shen, Nicholas Clark, Tanushree Mitra

Existing research primarily evaluates the values of LLMs by examining their stated inclinations towards specific values. However, the "Value-Action Gap," a phenomenon rooted in env…