Best AI papers explained

203 Episoder

1. Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy

   Publisert: 8.5.2025
2. Decoding Claude Code: Terminal Agent for Developers

   Publisert: 7.5.2025
3. Emergent Strategic AI Equilibrium from Pre-trained Reasoning

   Publisert: 7.5.2025
4. Benefiting from Proprietary Data with Siloed Training

   Publisert: 6.5.2025
5. Advantage Alignment Algorithms

   Publisert: 6.5.2025
6. Asymptotic Safety Guarantees Based On Scalable Oversight

   Publisert: 6.5.2025
7. What Makes a Reward Model a Good Teacher? An Optimization Perspective

   Publisert: 6.5.2025
8. Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems

   Publisert: 6.5.2025
9. Identifiable Steering via Sparse Autoencoding of Multi-Concept Shifts

   Publisert: 6.5.2025
10. You Are What You Eat - AI Alignment Requires Understanding How Data Shapes Structure and Generalisation

    Publisert: 6.5.2025
11. Interplay of LLMs in Information Retrieval Evaluation

    Publisert: 3.5.2025
12. Trade-Offs Between Tasks Induced by Capacity Constraints Bound the Scope of Intelligence

    Publisert: 3.5.2025
13. Toward Efficient Exploration by Large Language Model Agents

    Publisert: 3.5.2025
14. Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT

    Publisert: 2.5.2025
15. Self-Consuming Generative Models with Curated Data

    Publisert: 2.5.2025
16. Bootstrapping Language Models with DPO Implicit Rewards

    Publisert: 2.5.2025
17. DeepSeek-Prover-V2: Advancing Formal Reasoning

    Publisert: 1.5.2025
18. THINKPRM: Data-Efficient Process Reward Models

    Publisert: 1.5.2025
19. Societal Frameworks and LLM Alignment

    Publisert: 29.4.2025
20. Risks from Multi-Agent Advanced AI

    Publisert: 29.4.2025