9 citations · 13 across the 6 of their papers we have counts for
6 papers
The Ideation Bottleneck: Decomposing the Quality Gap Between AI-Generated and Human Economics Research
Ning Li
Autonomous AI systems can now generate complete economics research papers, but they substantially underperform human-authored publications in head-to-head comparisons. This paper d…
LLMs learn scientific taste from institutional traces across the social sciences
Ziqin Gong, Ning Li, Huaikang Zhou
Reinforcement-learned reasoning has powered recent AI leaps on verifiable tasks, including mathematics, code, and structure prediction. The harder bottleneck is evaluative judgment…
HybridEP: Scaling Expert Parallelism to Cross-Datacenter Scenario via Hybrid Expert/Data Transmission
Weihao Yang, Hao Huang, Donglei Wu +6
Mixture-of-Experts (MoE) has become a popular architecture for scaling large models. However, the rapidly growing scale outpaces model training on a single DC, driving a shift towa…
Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management
Ziyan Cui, Ning Li, Huaikang Zhou
Artificial Intelligence (AI) is increasingly being integrated into scientific research, particularly in the social sciences, where understanding human behavior is critical. Large L…
From Text to Insight: Leveraging Large Language Models for Performance Evaluation in Management
Ning Li, Huaikang Zhou, Mingze Xu
This study explores the potential of Large Language Models (LLMs), specifically GPT-4, to enhance objectivity in organizational task performance evaluations. Through comparative an…
Generative AI Enhances Team Performance and Reduces Need for Traditional Teams
Ning Li, Huaikang Zhou, Kris Mikel-Hong
Recent advancements in generative artificial intelligence (AI) have transformed collaborative work processes, yet the impact on team performance remains underexplored. Here we exam…