Austin, TX
United States
University of Texas at Austin - McCombs School of Business
SSRN RANKINGS
in Total Papers Downloads
Recommender systems, Heterogeneous information, Matrix completion, Geometric deep learning, Representation learning, Interpretable machine learning, Large language model, Generative AI, Explainable recommender systems
Generative AI, LLMs, Economic decision-making, Mental accounting, Prospect theory, Heuristics and biases, Loss aversion
large language model, calibration, preference learning, opinion learning, data collection, LLM-based measurement, preference measurement, opinion measurement, synthetic respondents
pure exploration, information acquisition, transductive learning, short-form video platforms, recommender systems
Causal inference, Heterogeneous treatment effects, Random experiments, Calibration, Machine learning
Hypergraph, Higher Order Dynamics, Centrality, Information Flow, Information Systems
Data acquisition, recommender system, design science, consumer network, machine learning
Large Language Models, Mental Accounting, Behavioral Biases, Mechanistic Interpretability, Linear Representation
information presentation, deep learning, spatio-temporal learning, ordinary differential equations, delivery time prediction
Data Governance, Data Value, Machine Unlearning, Fine-Tuning, Influence Function
network privacy; network game; network learning; social network; differential privacy
large language models, text-as-data, measurement design, construct operationalization, prompt uncertainty
synthetic respondents, LLM-generated market research, hybrid measurement design, resource allocation under measurement cost, decision support, activation-level diagnostics
Travel time inference, Trajectory-free inference, Sparse tensor completion, Koopman operator, Adaptive filtering, Uncertainty quantification
large language models, hypothesis generation, graphs, centrality
Local market structure; Networks; Complements and substitutes; Centrality measures
