Autumn Toney

According to our database, Autumn Toney authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2024

Climate change and artificial intelligence: assessing the global research landscape.

Joanna I. Lewis, Autumn Toney, Xinglan Shi

Discov. Artif. Intell., 2024

AI on AI: Exploring the Utility of GPT as an Expert Annotator of AI Publications.

Autumn Toney-Wails, Christian Schoeberl, James Dunham

CoRR, 2024

Are You Sure About That: Eliciting Natural Language Confidence Indicators from Chatbots.

Autumn Toney-Wails, Lisa Singh

Proceedings of the 12th International Conference on Human-Agent Interaction, 2024

Trust Issues: Discrepancies in Trustworthy AI Keywords Use in Policy and Research.

Autumn Toney, Kathleen Curlee, Emelia Probasco

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Let Me Generate That for You: Generative Data Augmentation for Misinformation Detection in Low-Resource Environments.

Autumn Toney-Wails, Lisa Singh

Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

2023

Investigating Scientific Misinformation Using Different Modes of Learning.

Autumn Toney-Wails, Kornraphop Kawintiranon, Lisa Singh, Paul-Emmanuel Courtines, Alexander Lin, Haofei Zhang

Proceedings of the Workshop on Scientific Document Understanding co-located with 37th AAAI Conference on Artificial Inteligence (AAAI 2023), 2023

2022

Multi-label Classification of Scientific Research Documents Across Domains and Languages.

Autumn Toney, James Dunham

Proceedings of the Third Workshop on Scholarly Document Processing, 2022

2021

AI Research Funding Portfolios and Extreme Growth.

Ilya Rahkovsky, Autumn Toney, Kevin W. Boyack, Richard Klavans, Dewey A. Murdick

Frontiers Res. Metrics Anal., 2021

A Large-Scale, Automated Study of Language Surrounding Artificial Intelligence.

Autumn Toney

CoRR, 2021

Automatically Characterizing Targeted Information Operations Through Biases Present in Discourse on Twitter.

Autumn Toney, Akshat Pandey, Wei Guo, David A. Broniatowski, Aylin Caliskan

Proceedings of the 15th IEEE International Conference on Semantic Computing, 2021

ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries.

Autumn Toney, Aylin Caliskan

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades.

Autumn Toney, Aylin Caliskan

CoRR, 2020

Pro-Russian Biases in Anti-Chinese Tweets about the Novel Coronavirus.

Autumn Toney, Akshat Pandey, Wei Guo, David A. Broniatowski, Aylin Caliskan

CoRR, 2020