9 papers
Revibing Code from Papers: Reimplementing HCI Artifacts
Eytan Adar, Yoonjoo Lee, Ning-Er +4
Software artifacts for most technical HCI research projects are unavailable. The lack of access to these imposes limits on academic knowledge production. It is difficult to: extend…
Evaluating Affective Objectives: Statistical Numbing in Data Visualization
Elsie Lee-Robbins, Eytan Adar
Visualizations can help audiences understand the scale of tragedies, such as the consequences of natural disasters, war, genocide, and pandemics. In these cases, a visualization de…
Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms
Joshua Ashkinaze, Ruijia Guan, Laura Kurek +3
Large language models (LLMs) are trained on broad corpora and then used in communities with specialized norms. Is providing LLMs with community rules enough for models to follow th…
Beyond Screenshots: Evaluating VLMs' Understanding of UI Animations
Chen Liang, Xirui Jiang, Naihao Deng +2
AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality, animations are increasingly…
Assessing Affective Objectives for Communicative Visualizations
Elsie Lee-Robbins, Eytan Adar
Using learning objectives to define designer intents for communicative visualizations can be a powerful design tool. Cognitive and affective objectives are concrete and specific, w…
Through the Judge's Eyes: Inferred Thinking Traces Improve Reliability of LLM Raters
Xingjian Zhang, Tianhong Gao, Suliang Jin +4
Large language models (LLMs) are increasingly used as raters for evaluation tasks. However, their reliability is often limited for subjective tasks, when human judgments involve su…