15 citations · 25 across the 7 of their papers we have counts for
7 papers
Epistemic Traps: Rational Misalignment Driven by Model Misspecification
Xingcheng Xu, Jingjing Qu, Qiaosheng Zhang +4
The rapid deployment of Large Language Models and AI agents across critical societal and technical domains is hindered by persistent behavioral pathologies including sycophancy, ha…
Deep Learning for Multi-Country GDP Prediction: A Study of Model Performance and Data Impact
Huaqing Xie, Xingcheng Xu, Fangjia Yan +2
GDP is a vital measure of a country's economic health, reflecting the total value of goods and services produced. Forecasting GDP growth is essential for economic planning, as it h…
Optimal Trade and Industrial Policies in the Global Economy: A Deep Learning Framework
Zi Wang, Xingcheng Xu, Yanqing Yang +1
We propose a deep learning framework, DL-opt, designed to efficiently solve for optimal policies in quantifiable general equilibrium trade models. DL-opt integrates (i) a nested fi…
Machine Learning for Economic Forecasting: An Application to China's GDP Growth
Yanqing Yang, Xingcheng Xu, Jinfeng Ge +1
This paper aims to explore the application of machine learning in forecasting Chinese macroeconomic variables. Specifically, it employs various machine learning models to predict t…
Principled Understanding of Generalization for Generative Transformer Models in Arithmetic Reasoning Tasks
Xingcheng Xu, Zibo Zhao, Haipeng Zhang +1
Transformer-based models excel in various tasks but their generalization capabilities, especially in arithmetic reasoning, remain incompletely understood. Arithmetic tasks provide…
Large Language Models at Work in China's Labor Market
Qin Chen, Jinfeng Ge, Huaqing Xie +2
This paper explores the potential impacts of large language models (LLMs) on the Chinese labor market. We analyze occupational exposure to LLM capabilities by incorporating human e…
It Ain't That Bad: Understanding the Mysterious Performance Drop in OOD Generalization for Generative Transformer Models
Xingcheng Xu, Zihao Pan, Haipeng Zhang +1
Large language models (LLMs) have achieved remarkable proficiency on solving diverse problems. However, their generalization ability is not always satisfying and the generalization…