Best AI papers explained

436 Episodes

1. Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

   Published: 9/1/2025
2. On the Theoretical Limitations of Embedding-Based Retrieval

   Published: 8/31/2025
3. Performance Prediction for Large Systems via Text-to-Text Regression

   Published: 8/30/2025
4. Demystifying the Visual Quality Paradox in Multimodal Large Language Models

   Published: 8/30/2025
5. Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL

   Published: 8/30/2025
6. Compute-Optimal Scaling for Value-Based Deep RL

   Published: 8/25/2025
7. LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience

   Published: 8/23/2025
8. Signal and Noise: Evaluating Language Model Benchmarks

   Published: 8/23/2025
9. Breaking Feedback Loops in Recommender Systems with Causal Inference

   Published: 8/21/2025
10. RAG is Dead, Context Engineering is King: Building Reliable AI Systems

    Published: 8/20/2025
11. A Survey of Personalization: From RAG to Agent

    Published: 8/20/2025
12. Facilitating the Adoption of Causal Infer-ence Methods Through LLM-Empowered Co-Pilot

    Published: 8/19/2025
13. Performance Prediction for Large Systems via Text-to-Text Regression

    Published: 8/16/2025
14. Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning

    Published: 8/15/2025
15. DINOv3: Vision Models for Self-Supervised Learning

    Published: 8/15/2025
16. Agent Lightning: Training Any AI Agents with Reinforcement Learning

    Published: 8/14/2025
17. Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier

    Published: 8/14/2025
18. From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models

    Published: 8/12/2025
19. Is Chain-of-Thought Reasoning a Mirage?

    Published: 8/12/2025
20. Agentic Web: Weaving the Next Web with AI Agents

    Published: 8/11/2025