Best AI papers explained

527 Episodes

1. Accelerating Unbiased LLM Evaluation via Synthetic Feedback

   Published: 9/05/2025
2. Prediction-Powered Statistical Inference Framework

   Published: 9/05/2025
3. Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL

   Published: 9/05/2025
4. RM-R1: Reward Modeling as Reasoning

   Published: 9/05/2025
5. Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy

   Published: 8/05/2025
6. Decoding Claude Code: Terminal Agent for Developers

   Published: 7/05/2025
7. Emergent Strategic AI Equilibrium from Pre-trained Reasoning

   Published: 7/05/2025
8. Benefiting from Proprietary Data with Siloed Training

   Published: 6/05/2025
9. Advantage Alignment Algorithms

   Published: 6/05/2025
10. Asymptotic Safety Guarantees Based On Scalable Oversight

    Published: 6/05/2025
11. What Makes a Reward Model a Good Teacher? An Optimization Perspective

    Published: 6/05/2025
12. Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems

    Published: 6/05/2025
13. Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts

    Published: 6/05/2025
14. You Are What You Eat - AI Alignment Requires Understanding How Data Shapes Structure and Generalisation

    Published: 6/05/2025
15. Interplay of LLMs in Information Retrieval Evaluation

    Published: 3/05/2025
16. Trade-Offs Between Tasks Induced by Capacity Constraints Bound the Scope of Intelligence

    Published: 3/05/2025
17. Toward Efficient Exploration by Large Language Model Agents

    Published: 3/05/2025
18. Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT

    Published: 2/05/2025
19. Self-Consuming Generative Models with Curated Data

    Published: 2/05/2025
20. Bootstrapping Language Models with DPO Implicit Rewards

    Published: 2/05/2025