Report NEP-AIN-2026-11-02

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:

• Liu, Jing & Sweet, Tracy & Chen, Marty & Engelberg, Jonathan & Masters, Megan & Clark, Martyn & Persaud, Axel & Lancaster, Alia & Hollingsworth, Jeffrey & Rice, Jennifer, 2026, "The Effects of Course-Integrated AI Tutoring on Student Performance and Engagement: A Randomized University Trial," IZA Discussion Papers, IZA Network @ LISER, number 18989, Oct.
• Adi Tarabeih, 2026, "Prospect Theory in Large Language Models: A Meta-Analysis of Loss Aversion, Diminishing Sensitivity, and Probability Weighting," Papers, arXiv.org, number 2610.33103, Oct.
• Yuhang Ji & Fasheng Xu & Tianjun Feng, 2026, "Monetizing Intelligence: Advertising and Subscription Design on LLM Platforms," Papers, arXiv.org, number 2610.32945, Oct.
• Mark L. Egan & Dominic Russel & Claire Shi & Vincent Yao, 2026, "Competition in Generative AI: Evidence from Consumer Demand," NBER Working Papers, National Bureau of Economic Research, Inc, number 35953, Oct.
• Eduardo Levy Yeyati & Dar'io Judzik & Juan Ignacio Barbiero, 2026, "Practice Makes Perfect: Tacit Knowledge, Generative AI, and Returns to Schooling and Experience," Papers, arXiv.org, number 2610.36008, Oct.
• Vahagn Jerbashian & Montserrat Vilalta-Bufi, 2026, "AI at Work: Use, Complementary Technologies, and Task Reallocation," CESifo Working Paper Series, CESifo, number 13094.
• Joshua S. Gans & Peter Landry, 2026, "Training Your Replacement: Worker Incentives and the Pace of Automation," NBER Working Papers, National Bureau of Economic Research, Inc, number 35950, Oct.
• Marco Francesconi & Xiaoyu Xia, 2026, "AI and the Boundary of the Firm: Evidence from Radiology," CESifo Working Paper Series, CESifo, number 13086.
• Manish Jha & Jialin Qian & Michael Weber & Baozhong Yang, 2026, "Generative AI, Managerial Expectations, and Economic Activity," NBER Working Papers, National Bureau of Economic Research, Inc, number 35949, Oct.
• Fernández, Gastón P. & Rammer, Christian & Czarnitzki, Dirk, 2026, "AI Adoption by Firms: Insights from the Literature and the German Innovation Survey," IZA Discussion Papers, IZA Network @ LISER, number 18991, Oct.
• Alessandro Villa, 2026, "AI, Expectations, and Optimal Interest Rates," Working Paper Series, Federal Reserve Bank of Chicago, number WP 2026-21, Oct, DOI: 10.21033/wp-2026-21.
• Jin Huang & Diego Ferreras Garrucho & Yutong Xie & Walter M. Yuan & Qiaozhu Mei & Chen Lian & Jonathon Hazell, 2026, "HouseholdBench: Evaluating Large Language Models as Predictors of Household Economic Behavior," NBER Working Papers, National Bureau of Economic Research, Inc, number 35927, Oct.
• Bhagwat, Vineet & Cookson, J. Anthony & Dim, Chukwuma Chijioke & Niessner, Marina, 2026, "The market's mirror: Revealing investor disagreement with LLMS," Working Papers, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State, number 390.
• Buchetti, Bruno & Lin, Luca X. & Miquel-Flores, Ixart & Eufinger, Christian, 2026, "Headwind or tailwind? How banks interpret borrowers’ AI exposure," Working Paper Series, European Central Bank, number 3302, Oct.
• Giorgos Iacovides & Oliver Hannibal & Wuyang Zhou & Danilo Mandic, 2026, "FinLLM-KG: Knowledge Graph-Enhanced LLMs for Financial Sentiment Analysis in Algorithmic Trading," Papers, arXiv.org, number 2610.36083, Oct.
• Javier Ojea Ferreiro & Andrea Ugolini & Juan C. Reboredo, 2026, "Artificial Intelligence and Financial Tail Risks," Staff Working Papers, Bank of Canada, number 26-40, Oct, DOI: 10.34989/swp-2026-40.