6 papers
From Words to Widgets for Controllable LLM Generation
Chao Zhang, Yiren Liu, Lunyiu Nie +3
Natural language remains the predominant way people interact with large language models (LLMs). However, users often struggle to precisely express and control subjective preference…
Priming, Path-dependence, and Plasticity: Understanding the molding of user-LLM interaction and its implications from (many) chat logs in the wild
Shengqi Zhu, Jeffrey M. Rzeszotarski, David Mimno
User interactions with LLMs are shaped by prior experiences and individual exploration, but in-lab studies do not provide system designers with visibility into these in-the-wild fa…
Embodying Facts, Figures, and Faiths in Narrative Artistic Performances in Rural Bangladesh
Sharifa Sultana, Zinnat Sultana, Jeffrey M. Rzeszotarski +1
There is an increasing interest in telling serious stories with data. Designers organize information, construct narratives, and present findings to inform audiences. However, many…
Fairness-in-the-Workflow: How Machine Learning Practitioners at Big Tech Companies Approach Fairness in Recommender Systems
Jing Nathan Yan, Emma Harvey, Junxiong Wang +2
Recommender systems (RS), which are widely deployed across high-stakes domains, are susceptible to biases that can cause large-scale societal impacts. Researchers have proposed met…
Show or Tell? Modeling the evolution of request-making in Human-LLM conversations
Shengqi Zhu, Jeffrey M. Rzeszotarski, David Mimno
Designing user-centered LLM systems requires understanding how people use them, but patterns of user behavior are often masked by the variability of queries. In this work, we intro…
What We Talk About When We Talk About LMs: Implicit Paradigm Shifts and the Ship of Language Models
Shengqi Zhu, Jeffrey M. Rzeszotarski
The term Language Models (LMs) as a time-specific collection of models of interest is constantly reinvented, with its referents updated much like the rep…