collaborators

7 papers

cs.HC2026

AI Adoption Across a Multinational Workforce: Sociotechnical Conditions for GenAI Acceptance in Human Resources

Dalia Ali, Maria José Rodríguez Velázquez, Manoel Horta Ribeiro +2

Generative AI (GenAI) deployment in the workplace is accelerating rapidly. Nevertheless, questions of who adopts, who benefits, and who is left behind and why are still understudie…

cs.HC2026

AI Assistance for Discretionary Work: Increasing Feedback Provision in Higher Education

Romina Mahinpei, Victoria Dean, Ruth Fong +2

AI systems increasingly shape human workflows by generating intermediate artifacts that users can adopt, revise, or ignore. While prior work has shown that AI assistance can improv…

cs.HC2026

When LLMs Help -- and Hurt -- Teaching Assistants in Proof-Based Courses

Romina Mahinpei, Sofiia Druchyna, Manoel Horta Ribeiro

Teaching assistants (TAs) are essential to grading and feedback provision in proof-based courses, yet these tasks are time-intensive and difficult to scale. Although Large Language…

cs.SI2026

Hiding Liker Identity Did Not Increase Engagement With Reputationally Risky Content on X (Formerly Twitter)

Yuwei Chuai, Manoel Horta Ribeiro, Gabriele Lenzini +1

In June 2024, X (formerly Twitter) made likes from public to private, offering a rare, platform-level opportunity to study how the visibility of engagement signals affects users' b…

cs.CL2025

Accumulating Context Changes the Beliefs of Language Models

Jiayi Geng, Howard Chen, Ryan Liu +4

Language model (LM) assistants are increasingly used in applications such as brainstorming and research. Improvements in memory and context size have allowed these models to become…

cs.CY2025

When Incentives Backfire, Data Stops Being Human

Sebastin Santy, Prasanta Bhattacharya, Manoel Horta Ribeiro +2

Progress in AI has relied on human-generated data, from annotator marketplaces to the wider Internet. However, the widespread use of large language models now threatens the quality…