activity
20242026
most citedtAIfa: Enhancing Team Effectiveness and Cohesion with AI-Generated Automated Feedback

9 citations · 20 across the 21 of their papers we have counts for

collaborators

24 papers

cs.HC2026

CoBranchMR: Supporting Parallel Design and Conflict Resolution in Mixed Reality

Niloofar Sayadi, Kaiyuan Tang, Yunhao Xing +3

We present CoBranchMR, a mixed reality (MR) system that enables distributed collaborators to work in parallel from different locations on the same digital representation of a physi…

cs.CE2026

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Lois Curfman McInnes, Dorian Arnold, Prasanna Balaprakash +45

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only co…

cs.CY2026

Framing War Across Languages: Power, Agency, and Sentiment in Wikipedia's Multilingual War Narratives

Jiarui Xia, Diego Gomez-Zara

While Wikipedia promotes a neutral point of view on historical conflicts, its language editions are written by editors from distinct linguistic and cultural communities. In this st…

cs.HC2026

Stayin' Aligned Over Time: Towards Longitudinal Human-LLM Alignment via Contextual Reflection and Privacy-Preserving Behavioral Data

Simret Araya Gebreegziabher, Allison E Sproul, Yinuo Yang +3

Current human-AI alignment and evaluation methods for large language models (LLMs) often rely on preference signals collected immediately after an interaction. This practice implic…

cs.HC2026

MultEval: Supporting Collaborative Alignment for LLM-as-a-Judge Evaluation Criteria

Charles Chiang, Simret Gebreegziabher, Annalisa Szymanski +6

LLM-as-a-judge approaches have emerged as a scalable solution for evaluating model behaviors, yet they rely on evaluation criteria often created by a single individual, embedding t…

cs.HC2026

Revisiting Framing Codebooks with AI: Employing Large Language Models as Analytical Collaborators in Deductive Content Analysis

Diego Gomez-Zara, Hernán Valdivieso, Jorge Pérez +2

Codebooks are central to framing research, providing theoretically grounded criteria for analyzing news content. While traditionally codebooks are built from theoretical frameworks…