Printed from https://ideas.repec.org/n/nep-big/2025-02-24.html
Report NEP-BIG-2025-02-24
This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé (Tom Coupe) issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-BIG
The following items were announced in this report:
- Zhouyu Shen & Dacheng Xiu, 2025, "Can Machines Learn Weak Signals?," NBER Working Papers, National Bureau of Economic Research, Inc, number 33421, Jan.
- Kubitza, Dennis Oliver & Weßling, Katarina, 2025, "Whole Lotta Training - Studying School-to-Training Transitions by Training Artificial Neural Networks," EconStor Preprints, ZBW - Leibniz Information Centre for Economics, number 310974.
- Item repec:osf:africa:vpuac_v1 is not listed on IDEAS anymore
- Yoontae Hwang & Yaxuan Kong & Stefan Zohren & Yongjae Lee, 2025, "Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization," Papers, arXiv.org, number 2502.00828, Feb.
- Kim, Soonho & Song, Xingyi & Park, Boyeong & Ko, Daeun & Liu, Yanyan, 2024, "Real-time media analysis using large language model (LLM) for the top 5 prioritized pests and diseases," CGIAR Initative Publications, International Food Policy Research Institute (IFPRI), number Plant Health.
- Matthew Caron & Oliver Müller & Johannes Kriebel, 2025, "Detecting and Mitigating Shortcut Learning Bias in Machine Learning: A Pathway to More Generalizable ML-based (IS) Research," Working Papers Dissertations, Paderborn University, Faculty of Business Administration and Economics, number 129, Feb.
- Chowdhury, Koushik, 2023, "Towards a Deep Learning approach to regularise discourse of collaborative learner," Thesis Commons, Center for Open Science, number hjk4b_v1, May, DOI: 10.31219/osf.io/hjk4b_v1.
- Robin Jarry & Marc Chaumont & Laure Berti-Equille & Gérard Subsol, 2024, "Predicting Socio-economic Indicator Variations with Satellite Image Time Series and Transformer," Post-Print, HAL, number lirmm-04895134, Nov.
- Pilar García & Diego Torres, 2025, "Perceiving central bank communications through press coverage," Working Papers, Banco de España, number 2505, Jan, DOI: https://doi.org/10.53479/38922.
- de Avila, Rogerio, 2024, "Utilizing Big Administrative Data in Evaluation Research: Integrating Causal Modeling, Program Theory, and Machine Learning," Thesis Commons, Center for Open Science, number z7der_v1, Nov, DOI: 10.31219/osf.io/z7der_v1.
- Di Zhang, 2025, "Efficient Triangular Arbitrage Detection via Graph Neural Networks," Papers, arXiv.org, number 2502.03194, Feb, revised Oct 2025.
- Felix Drinkall & Janet B. Pierrehumbert & Stefan Zohren, 2025, "When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks," Papers, arXiv.org, number 2502.02199, Feb.
- Joshua Rosaler & Luca Candelori & Vahagn Kirakosyan & Kharen Musaelian & Ryan Samson & Martin T. Wells & Dhagash Mehta & Stefano Pasquali, 2025, "Supervised Similarity for High-Yield Corporate Bonds with Quantum Cognition Machine Learning," Papers, arXiv.org, number 2502.01495, Feb.
- Item repec:osf:africa:pfrhx_v1 is not listed on IDEAS anymore
- Leila Pereira & Rafael Pucci & Rodrigo R. Soares, 2025, "Landing on Water: Air Interdiction, Drug-Trafficking Displacement, and Violence in the Brazilian Amazon," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2025_03, Apr.
- Lionel Fontagné & Francesca Micocci & Armando Rungi, 2025, "The heterogeneous impact of the EU-Canada agreement with causal machine learning," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number halshs-04913313, Jan.
- Pataranutaporn, Pat & Powdthavee, Nattavudh & Maes, Pattie, 2025, "Can AI Solve the Peer Review Crisis? A Large-Scale Experiment on LLM's Performance and Biases in Evaluating Economics Papers," IZA Discussion Papers, IZA Network @ LISER, number 17659, Jan.
- George Fatouros & Kostas Metaxas & John Soldatos & Manos Karathanassis, 2025, "MarketSenseAI 2.0: Enhancing Stock Analysis through LLM Agents," Papers, arXiv.org, number 2502.00415, Feb, revised Oct 2025.
- Iuliia Alekseenko & Dmitry Dagaev & Sofia Paklina & Petr Parshakov, 2025, "Strategizing with AI: Insights from a Beauty Contest Experiment," Papers, arXiv.org, number 2502.03158, Feb, revised Oct 2025.
- Daniil Karzanov & Rub'en Garz'on & Mikhail Terekhov & Caglar Gulcehre & Thomas Raffinot & Marcin Detyniecki, 2025, "Regret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards," Papers, arXiv.org, number 2502.02619, Feb.
- Victor Chernozhukov & Mert Demirer & Esther Duflo & Iv'an Fern'andez-Val, 2025, "Comment on "Sequential validation of treatment heterogeneity" and "Comment on generic machine learning inference on heterogeneous treatment effects in randomized experiments"," Papers, arXiv.org, number 2502.01548, Feb, revised Feb 2025.
- Thierry Mayer & Hillel Rapoport & Camilo Umana-Dajud, 2024, "Free Trade Agreements and the movement of business people," PSE Working Papers, HAL, number halshs-04721181, Oct.