Best AI papers explained

153 Episodes

1. Explainable Data-driven Share-of-choice Product Line Design Optimization

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Published: 4/10/2025
18. All Roads Lead to Likelihood: RL for Fine-Tuning Value

    Published: 4/8/2025
19. ATLAS: Tuning Agents via Critical Step Learning

    Published: 4/8/2025
20. Thinking Faster by Writing Less: Chain of Draft Reasoning

    Published: 4/8/2025