Best AI papers explained

456 Episodes

1. Machine Learning for Hypothesis Generation in Social Science

   Published: 4/11/2025
2. Active Learning for Moral Preference Elicitation: Challenges and Nuances

   Published: 4/11/2025
3. Gradient-Based Surveys for Nonparametric Discrete Choice Experiments

   Published: 4/11/2025
4. Explainable Data-driven Share-of-choice Product Line Design Optimization

   Published: 4/11/2025
5. The More You Ask, the Less You Get: When Additional Questions Hurt External Validity

   Published: 4/11/2025
6. Conjoint topics from Handbook of Marketing Analytics: Methods and Applications

   Published: 4/11/2025
7. Choice-Based Conjoint Analysis: Methods and Applications

   Published: 4/11/2025
8. Beyond Conjoint Analysis: The Future of Preference Measurement

   Published: 4/11/2025
9. An Optimization Framework for Adaptive Questionnaire Design

   Published: 4/11/2025
10. Adaptive Self-Explication of Multiattribute Preferences

    Published: 4/11/2025
11. Conjoint Analysis: Methods, Applications, and Recent Developments

    Published: 4/11/2025
12. Current Issues and a “Wish List” for Conjoint Analysis

    Published: 4/11/2025
13. Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis

    Published: 4/11/2025
14. Adaptive Polyhedral Methods for Conjoint Analysis

    Published: 4/11/2025
15. MSL: Enhancing LLM Recommenders via Masked Softmax Loss

    Published: 4/11/2025
16. Self-Supervised Deep Reinforcement Learning for Optimal Question Ranking

    Published: 4/11/2025
17. Adaptive Language Elicitation for Latent Information Discovery

    Published: 4/10/2025
18. LLM Persona Bias: Promise and Peril in Simulation

    Published: 4/10/2025
19. AutoTools: Automating Tool Use for Large Language Models

    Published: 4/10/2025
20. Tool Learning with Large Language Models: A Comprehensive Survey

    Published: 4/10/2025