Best AI papers explained
Ein Podcast von Enoch H. Kang
508 Folgen
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Breaking Feedback Loops in Recommender Systems with Causal Inference
Vom: 21.8.2025 -
RAG is Dead, Context Engineering is King: Building Reliable AI Systems
Vom: 20.8.2025 -
A Survey of Personalization: From RAG to Agent
Vom: 20.8.2025 -
Facilitating the Adoption of Causal Infer-ence Methods Through LLM-Empowered Co-Pilot
Vom: 19.8.2025 -
Performance Prediction for Large Systems via Text-to-Text Regression
Vom: 16.8.2025 -
Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Vom: 15.8.2025 -
DINOv3: Vision Models for Self-Supervised Learning
Vom: 15.8.2025 -
Agent Lightning: Training Any AI Agents with Reinforcement Learning
Vom: 14.8.2025 -
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier
Vom: 14.8.2025 -
From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models
Vom: 12.8.2025 -
Is Chain-of-Thought Reasoning a Mirage?
Vom: 12.8.2025 -
Agentic Web: Weaving the Next Web with AI Agents
Vom: 11.8.2025 -
The Assimilation-Accommodation Gap in LLM Intelligence
Vom: 10.8.2025 -
The Minimalist AI Kernel: A New Frontier in Reasoning
Vom: 6.8.2025 -
Statistical Rigor for Interpretable AI
Vom: 6.8.2025 -
Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value
Vom: 4.8.2025 -
A foundation model to predict and capture human cognition
Vom: 4.8.2025 -
Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
Vom: 4.8.2025 -
Hierarchical Reasoning Model
Vom: 4.8.2025 -
Test-time Offline Reinforcement Learning on Goal-related Experience
Vom: 4.8.2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
