most citedEvalet: Evaluating Large Language Models through Functional Fragmentation

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cs.HC20261 cited

Evalet: Evaluating Large Language Models through Functional Fragmentation

Tae Soo Kim, Heechan Lee, Yoonjoo Lee +2

Practitioners increasingly rely on Large Language Models (LLMs) to evaluate generative AI outputs through "LLM-as-a-Judge" approaches. However, these methods produce holistic score…

cs.HC20261 cited

Fostering Collective Discourse: A Distributed Role-Based Approach to Online News Commenting

Yoojin Hong, Yersultan Doszhan, Joseph Seering

Current news commenting systems are designed based on implicitly individualistic assumptions, where discussion is the result of a series of disconnected opinions. This often result…

cs.HC20261 cited

Botender: Supporting Communities in Collaboratively Designing AI Agents through Case-Based Provocations

Tzu-Sheng Kuo, Sophia Liu, Quan Ze Chen +4

AI agents, or bots, serve important roles in online communities. However, they are often designed by outsiders or a few tech-savvy members, leading to bots that may not align with…

cs.HC2025

How Far I'll Go: Imagining Futures of Conversational AI with People with Visual Impairments Through Design Fiction

Jeanne Choi, Dasom Choi, Sejun Jeong +2

People with visual impairments (PVI) use a variety of assistive technologies to navigate their daily lives, and conversational AI (CAI) tools are a growing part of this toolset. Mu…

cs.HC2025

Prototyping Digital Social Spaces through Metaphor-Driven Design: Translating Spatial Concepts into an Interactive Social Simulation

Yoojin Hong, Martina Di Paola, Braahmi Padmakumar +3

Social media platforms are central to communication, yet their designs remain narrowly focused on engagement and scale. While researchers have proposed alternative visions for onli…