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Best AI papers explained

En podcast av: Enoch H. Kang

Cut through the noise. We curate and break down the most important AI papers so you don’t have to

Our American listeners can also listen to Best AI papers explained at our American site

430 Avsnitt

LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience
Publicerades 2025-08-23

Signal and Noise: Evaluating Language Model Benchmarks
Publicerades 2025-08-23
Breaking Feedback Loops in Recommender Systems with Causal Inference
Publicerades 2025-08-21
RAG is Dead, Context Engineering is King: Building Reliable AI Systems
Publicerades 2025-08-20
A Survey of Personalization: From RAG to Agent
Publicerades 2025-08-20
Facilitating the Adoption of Causal Infer-ence Methods Through LLM-Empowered Co-Pilot
Publicerades 2025-08-19
Performance Prediction for Large Systems via Text-to-Text Regression
Publicerades 2025-08-16
Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
Publicerades 2025-08-15
DINOv3: Vision Models for Self-Supervised Learning
Publicerades 2025-08-15
Agent Lightning: Training Any AI Agents with Reinforcement Learning
Publicerades 2025-08-14
Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier
Publicerades 2025-08-14
From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models
Publicerades 2025-08-12
Is Chain-of-Thought Reasoning a Mirage?
Publicerades 2025-08-12
Agentic Web: Weaving the Next Web with AI Agents
Publicerades 2025-08-11
The Assimilation-Accommodation Gap in LLM Intelligence
Publicerades 2025-08-10
The Minimalist AI Kernel: A New Frontier in Reasoning
Publicerades 2025-08-06
Statistical Rigor for Interpretable AI
Publicerades 2025-08-06
Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value
Publicerades 2025-08-04
A foundation model to predict and capture human cognition
Publicerades 2025-08-04
Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
Publicerades 2025-08-04

Cut through the noise. We curate and break down the most important AI papers so you don’t have to.

430 Avsnitt

LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience

Signal and Noise: Evaluating Language Model Benchmarks

Breaking Feedback Loops in Recommender Systems with Causal Inference

RAG is Dead, Context Engineering is King: Building Reliable AI Systems

A Survey of Personalization: From RAG to Agent

Facilitating the Adoption of Causal Infer-ence Methods Through LLM-Empowered Co-Pilot

Performance Prediction for Large Systems via Text-to-Text Regression

Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning

DINOv3: Vision Models for Self-Supervised Learning

Agent Lightning: Training Any AI Agents with Reinforcement Learning

Computational-Statistical Tradeoffs at the Next-Token Prediction Barrier

From Model Weights to Agent Workflows: Charting the New Frontier of Optimization in Large Language Models

Is Chain-of-Thought Reasoning a Mirage?

Agentic Web: Weaving the Next Web with AI Agents

The Assimilation-Accommodation Gap in LLM Intelligence

The Minimalist AI Kernel: A New Frontier in Reasoning

Statistical Rigor for Interpretable AI

Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value

A foundation model to predict and capture human cognition

Generative Recommendation with Semantic IDs: A Practitioner’s Handbook