Reference change · event page
Reference changes · DOI
Correction
Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.
This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.
Correction
Crossref
31 open · 31 total · 0 disputed
- Event date
- 2024-03-06
01One-hop citing occurrences
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EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness
ref [17] ·
2605.01024
· notice #6991
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Chuangqi Li, Xinying Weng, Yifan Li, and Tianxin Zhang. 2025. https://doi.org/10.1080/10447318.2024.2338616 Multimodal learning engagement assessment system: An innovative approach to optimizing learning engagement . International Journal of Human--Computer Interaction, 41(5):3474--3490
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Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs
ref [110] ·
2604.19245
· notice #6993
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What. International Journal of Human–Computer Interaction , author =. doi:10.1080/10447318.2024.2443263 , abstract =
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What. International Journal of Human–Computer Interaction, author =. doi:10.1080/10447318.2024.2443263, abstract =
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From Prompts to Context: An Ontology-Driven Framework for Human-Generative AI Collaboration
ref [59] ·
2605.29675
· notice #7013
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Young Woo Kim, S.H.Y. Min Chul Cha, Lee, S.C.: Not merely useful but also amusing: Impact of perceived usefulness and perceived enjoyment on the adop- tion of ai-powered coding assistant. International Journal of Human–Computer Interaction0(0), 1–13 (2024) https://doi.org/10.1080/10447318.2024.2375701
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The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality
ref [26] ·
2604.20569
· notice #6992
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doi:10.1080/10447318.2024.2345430 Publisher: Taylor & Francis. The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality
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AttentionBender: Manipulating Cross-Attention in Video Diffusion Transformers as a Creative Probe
ref [52] ·
2604.20936
· notice #6989
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Jonas Oppenlaender, Rhema Linder, and Johanna Silvennoinen. 2025. Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering.Interna- tional Journal of Human–Computer Interaction41, 16 (Aug. 2025), 10207–10229. doi:10.1080/10447318.2024.2431761
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Results-Actionability Gap: Understanding How Practitioners Evaluate LLM Products in the Wild
ref [52] ·
2604.16304
· notice #7001
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Malak Sadek and Celine Mougenot. 2025. Challenges in Value-Sensitive AI Design: Insights from AI Practitioner Interviews.International Journal of Hu- man–Computer Interaction41, 17 (2025), 10877–10894. https://doi.org/10.1080/ 10447318.2024.2439021
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"It Felt a Bit Eerie": Exploring Humanlike Interactions During Collaborative Writing with an Artificial Agent
ref [105] ·
2605.24729
· notice #7015
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Jiyoun Seok, Brandon Hwansun Lee, Dongmi Kim, Sunyoung Bak, Saeyeong Kim, Sungtae Kim, and Somin Park. 2025. What Emotions and Personalities Determine Acceptance of Generative AI?: Focusing on the CASA Paradigm.International Journal of Human–Computer Interaction41, 18 (Sept. 2025), 11436–11458. doi:10.1080/10447318.2024.2443263
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Where's the Team Spirit? An Exploratory Study on Team Development Through Co-located Tablet-Based VR
ref [6] ·
2605.03127
· notice #6994
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Anthony Cherbonnier, Brivael Hémon, Nicolas Michinov, Eric Jamet, and Estelle Michinov. 2024. Collaborative Skills Training Using Digital Tools: A Systematic Literature Review.International Journal of Human–Computer Interaction(May 2024), 1–19. doi:10.1080/ 10447318.2024.2348227
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How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
ref [77] ·
2605.10898
· notice #6995
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Jonas Oppenlaender, Rhema Linder, and Johanna Silvennoinen. 2025. Prompt- ing AI Art: An Investigation into the Creative Skill of Prompt Engineer- ing.International Journal of Human–Computer Interaction0, 0 (2025), 1–23. https://doi.org/10.1080/10447318.2024.2431761
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How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
ref [46] ·
2605.10898
· notice #6996
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Soomin Kim, Jinsu Eun, Changhoon Oh, and Joonhwan Lee. 2025. “Journey of Finding the Best Query”: Understanding the User Experience of AI Image Generation System.International Journal of Human–Computer Interaction41, 2 (Jan. 2025), 951–969. https://doi.org/10.1080/10447318.2024.2307670
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Adaptive Prompt Elicitation for Text-to-Image Generation
ref [41] ·
2602.04713
· notice #6998
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Soomin Kim, Jinsu Eun, Changhoon Oh, and Joonhwan Lee. 2025. “Journey of Finding the Best Query”: Understanding the User Experience of AI Image Generation System. International Journal of Human–Computer Interaction 41, 2 (2025), 951–969. doi:10.1080/10447318.2024.2307670
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"If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace
ref [107] ·
2602.01386
· notice #6999
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Auste Simkute, Lev Tankelevitch, Viktor Kewenig, Ava Elizabeth Scott, Abigail Sellen, and Sean Rintel. 2024. Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction.International Journal of Human–Computer Interaction(Oct. 2024), 1–22. doi:10.1080/10447318.2024. 2405782
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Measuring Machine Companionship: Scale Development and Validation for AI Companions
ref [2] ·
2511.00654
· notice #7003
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https://doi.org/10.1080/10447318.2024.2375797 Seibt, J., Vestergaard, C., & Damholdt, M. F. (2020). Sociomorphing, not anthropomorphizing: Towards a typology of experienced sociality. Proceedings of Robophilosophy 2020. 335, pp. 51-67. IOS Press. Shank, D. B. (2025). Providing companionship. In The machine penalty (pp. 171- 191). Springer. Sherry, A., & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: A user-friendly primer. Journal of Personality Assessment, 84(1), 37-48. Simondon, G. (1958/2017). On the mode of existence of technical objects. (C. Malaspina, & J. Rogove, Trans.) Univocal. Singles in America. (2025). The great relationship reset: What 5,000 singles taught us about connection. https://www.singlesinamerica.com/ Starke, C., Ventura, A., Bersch, C., Cha, M., de Vreese, C., Doebler, P., . . . Köbis, N. (2024). Risks and protective measures for synthetic relationships. Nature Human Behavior, 8, 1834-1836. https://doi.org/10.1038/s41562-024-02005-4 Sternberg, R. J. (1986). A triangular theory of love. Psychological Review, 93(2), 119-135. Suchman, L. (2007). Human-machine reconfigurations: Plans and situated actions
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How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insights
ref [8] ·
2603.03140
· notice #7004
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Helena Lindgren. Emerging roles and relationships among humans and interactive ai systems.International Journal of Human–Computer Interaction, 41(17):10595–10617, 2025. doi: 10.1080/10447318.2024.2435693. URL https://doi.org/10.1080/10447318.2024.2435693
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Same Scrutiny, More Time: Eye Tracking Insights into Reviewing LLM-Labelled Code
ref [43] ·
2606.26505
· notice #7005
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Auste Simkute, Lev Tankelevitch, Viktor Kewenig, Ava Elizabeth Scott, Abi- gail Sellen, and Sean Rintel. 2025. Ironies of Generative AI: Understand- ing and Mitigating Productivity Loss in Human-AI Interaction.Inter- national Journal of Human–Computer Interaction41, 5 (2025), 2898–2919. arXiv:https://doi.org/10.1080/10447318.2024.2405782 doi:10.1080/10447318.2024. 2405782
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A Test-time Actor-Critic Approach to News Images Generation
ref [8] ·
2606.21304
· notice #7006
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J. Oppenlaender, R. Linder, J. Silvennoinen, Prompting ai art: An investigation into the creative skill of prompt engineering, International Journal of Human–Computer Interaction 41 (2025) 10207–10229. doi:10.1080/10447318.2024.2431761
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Comparing Controller-Free Pointing Techniques Across Depth for 2D Selection in Augmented Reality
ref [20] ·
2606.08441
· notice #7007
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Ajoy S. Fernandes, Murdison , T. Scott, , and Michael J. Proulx. 2025. Looking in Depth: Targeting by Eye and Controller Input for Multi-Depth Target Placement. International Journal of Human–Computer Interaction41, 13 (July 2025). https: //doi.org/10.1080/10447318.2024.2401657 Publisher: Taylor & Francis, pages = 7952–7967,
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Ajoy S. Fernandes, Murdison, T. Scott,, and Michael J. Proulx. 2025. Looking in Depth: Targeting by Eye and Controller Input for Multi-Depth Target Placement. International Journal of Human–Computer Interaction41, 13 (July 2025). https: //doi.org/10.1080/10447318.2024.2401657 Publisher: Taylor & Francis, pages = 7952–7967
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From Prompts to Preferences: An Open-Source Platform for Generative AI-Enhanced Conjoint Analysis
ref [22] ·
2606.12972
· notice #7008
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J. Y eon, Y . Jung, Y . Baek, D. Lee, J. Shin, and W. Y . Chung, “User preferences on a generative AI user interface through a choice experiment,” International Journal of Human–Computer Interaction , vol. 41, no. 12, pp. 7626–7637, 2024, doi: 10.1080/10447318.2024.2400379
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J. Y eon, Y . Jung, Y . Baek, D. Lee, J. Shin, and W. Y . Chung, “User preferences on a generative AI user interface through a choice experiment,” International Journal of Human–Computer Interaction, vol. 41, no. 12, pp. 7626–7637, 2024, doi: 10.1080/10447318.2024.2400379
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From Prompts to Preferences: An Open-Source Platform for Generative AI-Enhanced Conjoint Analysis
ref [21] ·
2606.12972
· notice #7009
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M. Keil, L. V ervier, P . Brauner, and M. Ziefle, “Will you be watching me? A conjoint-based study on employee attitudes toward personal data usage in smart factories,”International Journal of Human–Computer Interaction, vol. 41, no. 16, pp. 10024–10044, 2024, doi: 10.1080/10447318.2024.2430494
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Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI
ref [26] ·
2605.31275
· notice #7010
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Warmth, Competence, and the Determinants of Trust in Artificial Intelli- gence: A Cross-Sectional Survey from China.International Journal of Human– Computer Interaction41, 8 (2025), 5024–5038. doi:10.1080/10447318.2024.2356909
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Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI
ref [58] ·
2605.31275
· notice #7011
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Ruilin Xiao, Mert Yazan, and Frederik B. I. Situmeang. 2025. Rethinking Conver- sation Styles of Chatbots from the Customer Perspective: Relationships between Conversation Styles of Chatbots, Chatbot Acceptance, and Perceived Tie Strength and Perceived Risk.International Journal of Human–Computer Interaction41, 2 (2025), 1343–1363. doi:10.1080/10447318.2024.2314348
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Typing Behavior in Human-LLM Interaction: Keystroke Dynamics Reveal Cognitive Effort During Prompting
ref [50] ·
2606.28090
· notice #7012
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Auste Simkute, Lev Tankelevitch, Viktor Kewenig, Ava Elizabeth Scott, Abigail Sellen, and Sean Rintel and. 2025. Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction.International Journal of Human–Computer Interaction41, 5 (2025), 2898–2919. doi:10.1080/10447318.2024.2405782
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Auditing LLM-Governed Social Robots with Culture-Specific Moral Gradients
ref [33] ·
2606.28345
· notice #7014
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Muhammad Umer Khan and Zühal Erden. 2024. A Systematic Review of Social Robots in Shopping Environments. International Journal of Human–Computer Interaction (2024), 1–22. doi:10.1080/10447318.2024.2426740
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Beliefs and Misconceptions around Integrated Conversational AI
ref [23] ·
2605.14849
· notice #7016
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Changhyun Lee and Kyungjin Cha and. 2024. Toward the Dynamic Relationship Between AI Transparency and Trust in AI: A Case Study on ChatGPT.International Journal of Human–Computer Interaction0, 0 (2024), 1–18. arXiv:https://doi.org/10.1080/10447318.2024.2405266 doi:10.1080/ 10447318.2024.2405266
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How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
ref [46] ·
2605.10898
· notice #7017
· dispute
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Soomin Kim, Jinsu Eun, Changhoon Oh, and Joonhwan Lee. 2025. “Journey of Finding the Best Query”: Understanding the User Experience of AI Image Generation System.International Journal of Human–Computer Interaction41, 2 (Jan. 2025), 951–969. https://doi.org/10.1080/10447318.2024.2307670
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How Creatives Approach GenAI Image Generation: Tensions Between Structured Guidance, Self-Experimentation, and Creative Autonomy
ref [77] ·
2605.10898
· notice #7018
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Jonas Oppenlaender, Rhema Linder, and Johanna Silvennoinen. 2025. Prompt- ing AI Art: An Investigation into the Creative Skill of Prompt Engineer- ing.International Journal of Human–Computer Interaction0, 0 (2025), 1–23. https://doi.org/10.1080/10447318.2024.2431761
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Vibe Visualizing: How Visualization Novices Try (and Fail) to Generate and Interpret Visualizations with Conversational AI
ref [55] ·
2606.08914
· notice #7019
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A. Simkute, L. Tankelevitch, V . Kewenig, A. E. Scott, A. Sellen, and S. Rintel. Ironies of generative AI: Understanding and mitigating productivity loss in human-AI interaction.International Journal of Human–Computer Interaction, 41(5):2898–2919, 2025. doi: 10.1080/ 10447318.2024.2405782 9
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GenAI in Software Engineering: The Role of Technology Acceptance Models
ref [19] ·
2604.27642
· notice #6997
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Young Woo Kim, Min Chul Cha, Sol Hee Yoon, and Seul Chan Lee. 2025. Not Merely Useful but Also Amusing: Impact of Perceived Usefulness and Perceived Enjoyment on the Adoption of AI-Powered Coding Assistant.International Journal of Human–Computer Interaction41, 10 (May 2025), 6210–6222. doi:10. 1080/10447318.2024.2375701
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AI Washing Inflates Expected Performance but Not Interaction Outcomes: An AI Placebo Study Using Fitts' Law
ref [39] ·
2605.00582
· notice #6990
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Sebastian A. C. Perrig, Nick von Felten, Beat Vollenwyder, and Klaus Opwis. 2025. Development and Psychometric Validation of a Positively Worded German Version of the System Usability Scale (SUS).International Journal of Human–Computer Interaction41, 16 (2025), 10399–10419. doi:10.1080/10447318.2024.2434720
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LLM Harms: A Taxonomy and Discussion
ref [148] ·
2512.05929
· notice #7002
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A. Simkute, L. Tankelevitch, V . Kewenig, A. E. Scott, A. Sellen, and S. Rintel, “Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions,” Int J Hum Comput Interact , vol. 41, no. 5, pp. 2898 –2919, Feb. 2024, doi: 10.1080/10447318.2024.2405782
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A. Simkute, L. Tankelevitch, V . Kewenig, A. E. Scott, A. Sellen, and S. Rintel, “Ironies of Generative AI: Understanding and mitigating productivity loss in human-AI interactions,” Int J Hum Comput Interact, vol. 41, no. 5, pp. 2898 –2919, Feb. 2024, doi: 10.1080/10447318.2024.2405782
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AI and My Values: User Perceptions of LLMs' Ability to Extract, Embody, and Explain Human Values from Casual Conversations
ref [94] ·
2601.22440
· notice #7000
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Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction.International Journal of Human–Computer Interaction 41, 5 (2024), 2898–2919. doi:10.1080/10447318.2024.2405782