Best AI papers explained

436 Episodo

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Publicado: 11/8/2025