Report NEP-AIN-2024-10-14

This is the archive for NEP-AIN, a report on new working papers in the area of Artificial Intelligence. Ben Greiner issued this report. It is usually issued weekly.

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Other reports in NEP-AIN

The following items were announced in this report:

• Bohren, Noah & Hakimov, Rustamdjan & Lalive, Rafael, 2024. "Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments," IZA Discussion Papers 17302, Institute of Labor Economics (IZA).
• Ziyan Cui & Ning Li & Huaikang Zhou, 2024. "Can AI Replace Human Subjects? A Large-Scale Replication of Psychological Experiments with LLMs," Papers 2409.00128, arXiv.org, revised Sep 2024.
• Jingru Jia & Zehua Yuan, 2024. "An Experimental Study of Competitive Market Behavior Through LLMs," Papers 2409.08357, arXiv.org, revised Oct 2024.
• Vikram Krishnaveti & Saannidhya Rawat, 2024. "GPT takes the SAT: Tracing changes in Test Difficulty and Math Performance of Students," Papers 2409.10750, arXiv.org.
• Leonardo Gambacorta & Han Qiu & Shuo Shan & Daniel M Rees, 2024. "Generative AI and labour productivity: a field experiment on coding," BIS Working Papers 1208, Bank for International Settlements.
• Lee, Jaehyun & Lim, Jihye & Hwang, Junseok & Lee, Junmin, 2024. "How workers let artificial intelligence recruit and dismiss?," 24th ITS Biennial Conference, Seoul 2024. New bottles for new wine: digital transformation demands new policies and strategies 302513, International Telecommunications Society (ITS).
• Ali Merali, 2024. "Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Translation," Papers 2409.02391, arXiv.org, revised Dec 2024.
• Yueling Huang, 2024. "The Labor Market Impact of Artificial Intelligence: Evidence from US Regions," IMF Working Papers 2024/199, International Monetary Fund.
• Alexander Bick & Adam Blandin & David Deming, 2024. "The Rapid Adoption of Generative AI," Working Papers 2024-027, Federal Reserve Bank of St. Louis.
• Doron Yeverechyahu & Raveesh Mayya & Gal Oestreicher-Singer, 2024. "The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot," Papers 2409.08379, arXiv.org.
• Francesco D'Alessandro & Enrico Santarelli & Marco Vivarelli, 2024. "The KSTE+I approach and the AI technologies," DISCE - Quaderni del Dipartimento di Politica Economica dipe0039, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
• Martin Obschonka & Moren Levesque, 2024. "A Market for Lemons? Strategic Directions for a Vigilant Application of Artificial Intelligence in Entrepreneurship Research," Papers 2409.08890, arXiv.org.
• Anthony Harding & Juan Moreno-Cruz, 2024. "Watts and Bots: The Energy Implications of AI Adoption," Papers 2409.06626, arXiv.org.
• Cristian Trout, 2024. "Insuring Uninsurable Risks from AI: The State as Insurer of Last Resort," Papers 2409.06672, arXiv.org.
• Oecd, 2024. "Detecting cartels for ex officio investigations," OECD Roundtables on Competition Policy Papers 311, OECD Publishing.
• Sandy Chen & Leqi Zeng & Abhinav Raghunathan & Flora Huang & Terrence C. Kim, 2024. "MoA is All You Need: Building LLM Research Team using Mixture of Agents," Papers 2409.07487, arXiv.org, revised Sep 2024.
• Shengkun Wang & Taoran Ji & Linhan Wang & Yanshen Sun & Shang-Ching Liu & Amit Kumar & Chang-Tien Lu, 2024. "StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction," Papers 2409.08281, arXiv.org.
• Junjie Li & Yang Liu & Weiqing Liu & Shikai Fang & Lewen Wang & Chang Xu & Jiang Bian, 2024. "MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model," Papers 2409.07486, arXiv.org.
• Samuel Chang & Andrew Kennedy & Aaron Leonard & John List, 2024. "12 Best Practices for Leveraging Generative AI in Experimental Research," Artefactual Field Experiments 00796, The Field Experiments Website.