Report NEP-AIN-2024-09-09

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:

• Brian Jabarian, 2024. "Large Language Models for Behavioral Economics: Internal Validity and Elicitation of Mental Models," Papers 2407.12032, arXiv.org.
• Villarino, Resti Tito & Villarino, Maureen Lorence, 2024. "Advancing Instrument Validation in Social Sciences: An AI-Powered Chatbot and Interactive Website based on a Research Instrument Validation Framework (RIVF)," SocArXiv rjyzg, Center for Open Science.
• Zachary Wojtowicz, 2024. "When and Why is Persuasion Hard? A Computational Complexity Result," Papers 2408.07923, arXiv.org.
• Teng Ye & Jingnan Zheng & Junhui Jin & Jingyi Qiu & Wei Ai & Qiaozhu Mei, 2024. "Using Artificial Intelligence to Unlock Crowdfunding Success for Small Businesses," Papers 2407.09480, arXiv.org.
• Yao Lu & Gordon M. Phillips & Jia Yang, 2024. "The Impact of Cloud Computing and AI on Industry Dynamics and Concentration," NBER Working Papers 32811, National Bureau of Economic Research, Inc.
• Bastani, Spencer & Waldenström, Daniel, 2024. "AI, Automation and Taxation," IZA Policy Papers 212, Institute of Labor Economics (IZA).
• Jon Danielsson & Andreas Uthemann, 2024. "Artificial intelligence and financial crises," Papers 2407.17048, arXiv.org.
• Haowei Ni & Shuchen Meng & Xupeng Chen & Ziqing Zhao & Andi Chen & Panfeng Li & Shiyao Zhang & Qifu Yin & Yuanqing Wang & Yuxi Chan, 2024. "Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach," Papers 2408.06634, arXiv.org, revised Nov 2024.
• Colliard, Jean-Edouard & Foucault, Thierry & Lovo, Stefano, 2022. "Algorithmic Pricing and Liquidity in Securities Markets," HEC Research Papers Series 1459, HEC Paris.
• Wee Ling Tan & Stephen Roberts & Stefan Zohren, 2024. "Deep Learning for Options Trading: An End-To-End Approach," Papers 2407.21791, arXiv.org.
• Andras Komaromi & Xiaomin Wu & Ran Pan & Yang Liu & Pablo Cisneros & Anchal Manocha & Hiba El Oirghi, 2024. "Enhancing IMF Economics Training: AI-Powered Analysis of Qualitative Learner Feedback," IMF Working Papers 2024/166, International Monetary Fund.
• Gregory Yampolsky & Dhruv Desai & Mingshu Li & Stefano Pasquali & Dhagash Mehta, 2024. "Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals," Papers 2408.06679, arXiv.org.