Best AI papers explained
Un podcast de Enoch H. Kang
515 Épisodes
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On the Theoretical Limitations of Embedding-Based Retrieval
Publié: 31/08/2025 -
Performance Prediction for Large Systems via Text-to-Text Regression
Publié: 30/08/2025 -
Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Publié: 30/08/2025 -
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Publié: 30/08/2025 -
Compute-Optimal Scaling for Value-Based Deep RL
Publié: 25/08/2025 -
LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience
Publié: 23/08/2025 -
Signal and Noise: Evaluating Language Model Benchmarks
Publié: 23/08/2025 -
Breaking Feedback Loops in Recommender Systems with Causal Inference
Publié: 21/08/2025 -
RAG is Dead, Context Engineering is King: Building Reliable AI Systems
Publié: 20/08/2025 -
A Survey of Personalization: From RAG to Agent
Publié: 20/08/2025 -
Facilitating the Adoption of Causal Infer-ence Methods Through LLM-Empowered Co-Pilot
Publié: 19/08/2025 -
Performance Prediction for Large Systems via Text-to-Text Regression
Publié: 16/08/2025 -
Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Publié: 15/08/2025 -
DINOv3: Vision Models for Self-Supervised Learning
Publié: 15/08/2025 -
Agent Lightning: Training Any AI Agents with Reinforcement Learning
Publié: 14/08/2025 -
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier
Publié: 14/08/2025 -
From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models
Publié: 12/08/2025 -
Is Chain-of-Thought Reasoning a Mirage?
Publié: 12/08/2025 -
Agentic Web: Weaving the Next Web with AI Agents
Publié: 11/08/2025 -
The Assimilation-Accommodation Gap in LLM Intelligence
Publié: 10/08/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
