Best AI papers explained

484 Episodes

1. Dual Goal Representations

   Published: 10/14/2025
2. Welcome to the Era of Experience

   Published: 10/14/2025
3. Value Flows: Flow-Based Distributional Reinforcement Learning

   Published: 10/14/2025
4. Self-Adapting Language Models

   Published: 10/12/2025
5. The Markovian Thinker

   Published: 10/12/2025
6. Moloch’s Bargain: emergent misalignment when LLMs compete for audiences

   Published: 10/12/2025
7. Transformer Predictor Dynamics and Task Diversity

   Published: 10/11/2025
8. Base models know how to reason, thinking models learn when

   Published: 10/11/2025
9. Spectrum tuning: Post-training for distributional coverage and in-context steerability

   Published: 10/11/2025
10. Understanding Prompt Tuning and In-Context Learning via Meta-Learning

    Published: 10/11/2025
11. MLPs Learn In-Context on Regression and Classification tasks

    Published: 10/11/2025
12. Is Pre-Training Truly Better than Meta-Learning?

    Published: 10/11/2025
13. Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models

    Published: 10/11/2025
14. Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs

    Published: 10/9/2025
15. Learning dynamics of LLM finetuning

    Published: 10/9/2025
16. Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF

    Published: 10/9/2025
17. OpenAI Agent Builder and n8n: Orchestrating Reasoning Versus Automating Process

    Published: 10/8/2025
18. Training Agents Inside of Scalable World Models

    Published: 10/8/2025
19. Small Language Models are the Future of Agentic AI

    Published: 10/7/2025
20. Activation Steering in Generative Settings via Contrastive Causal Mediation Analysis

    Published: 10/6/2025