University Of Toronto: Research Institution — Prolific Citations Library

Browse 7 peer-reviewed papers from University Of Toronto spanning Human-Computer Interaction (HCI), Appropriate reliance on LLM (2022–2025). Research powered by Prolific's high-quality participant data.

This page lists 7 peer-reviewed papers from researchers at University Of Toronto in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (7 of 7)

To rely or not to rely? evaluating interventions for appropriate reliance on large language models

Authors: JY Bo, S Wan, A Anderson

Year: 2025

Published in: Proceedings of the 2025 CHI Conference ..., 2025 - dl.acm.org

Institution: University of Toronto

Research Area: Appropriate reliance on LLM, Human-Computer Interaction (HCI), AI-assisted decision making.

Discipline: Human-Computer Interaction (HCI)

This paper explores the latest advancements and key trends in the field of Human-Computer Interaction (HCI), focusing on novel interfaces and user experience paradigms.

Citations: 25
Longitudinal Study on Social and Emotional Use of AI Conversational Agent

Authors: Mohit Chandra, Javier Hernandez, Gonzalo Ramos, Mahsa Ershadi, Ananya Bhattacharjee, Judith Amores, Ebele Okoli, Ann Paradiso, Shahed Warreth, Jina Suh

Year: 2025

Published in: ArXiv

Institution: Georgia Institute of Technology, Microsoft Research, University of Toronto, Microsoft

Research Area: Social and Emotional Human-AI Interaction, Psychosocial Effects of AI Chatbot Use

Discipline: Social Science

This study found that active use of conversational AI tools significantly increased perceived attachment, empathy, and emotional support from AI, while showing the potential for improving social and emotional interactions with proper safeguards.

Methods: Participants were divided into two groups: one group used conversational AI tools actively (AU, n=89), and a baseline group used AI and the internet regularly (BU, n=60). Emotional and social interaction measures were tracked over five weeks.

Key Findings: Perceived attachment towards AI, AI empathy, comfort in using AI for emotional support, stress management, and discussion of personal topics.

Sample Size: 149
Constraints on novel word learning in heritage speakers

Authors: Y Ge, A Rato, P Rebuschat, P Monaghan

Year: 2024

Published in: Frontiers

Institution: Lancaster University, NOVA University Lisbon, University of Toronto, University of Tübingen

Research Area: Psycholinguistics, Second Language Acquisition, Word Learning

Discipline: Psycholinguistics, Second Language Acquisition, Word Learning
Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception

Authors: Harsh Kumar, Ilya Musabirov, Mohi Reza, Jiakai Shi, Xinyuan Wang, Joseph Jay Williams, Anastasia Kuzminykh, Michael Liut

Year: 2024

Published in: ArXiv

Institution: University of Toronto

Research Area: Educational Technology, Human-Computer Interaction (HCI), or Artificial Intelligence in Education.

Discipline: Educational Technology
When do annotator demographics matter? measuring the influence of annotator demographics with the POPQUORN dataset

Authors: J Pei, D Jurgens

Year: 2023

Published in: arXiv preprint arXiv:2306.06826, 2023 - arxiv.org

Institution: University of Michigan, University of Toronto

Research Area: Natural Language Processing (NLP)

Discipline: Natural Language Processing, Human-Computer Interaction (HCI)

DOI: https://doi.org/10.48550/arXiv.2306.06826

Citations: 55
When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being

Authors: H Kumar, J Chahal, Y Zhao, Z Zhang, A Wei

Year: 2023

Published in: arXiv preprint arXiv ..., 2025 - arxiv.org

Institution: University of Toronto, Harvard University

Research Area: AI and Well-Being, Human-AI Interaction, Online Advice-Seeking

Discipline: Artificial Intelligence, Human-Computer Interaction (HCI), Behavioral Science
Large language models are not zero-shot communicators

Authors: LE Ruis, A Khan, S Biderman, S Hooker, T Rocktäschel

Year: 2022

Published in: 2022 - openreview.net

Institution: MILA, University of Toronto, Stanford University, Hugging Face, Imperial College London

Research Area: Natural Language Processing, LLM, Communication

Discipline: Natural Language Processing

Citations: 52