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Best AI papers explained

Por: Enoch H. Kang

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

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Latest episodes of the podcast Best AI papers explained

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Statistical Inference for Online Algorithms 31/05/2025

Prismatic Synthesis for Diverse LLM Reasoning Data 31/05/2025

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents 31/05/2025

The Agentic Economy 30/05/2025

Statistics for Large Language Models 29/05/2025

Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search 29/05/2025

Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM Reasoning 29/05/2025

Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL 29/05/2025

Value-Guided Search for Efficient Chain-of-Thought Reasoning 29/05/2025

Shallow Preference Signals: Large Language model aligns even better without truncated data? 29/05/2025

Gaming Tool Preferences in Agentic LLMs 29/05/2025

Partner Modelling Emerges in Recurrent Agents (But Only When It Matters) 29/05/2025

LLM Populations Form Social Conventions and Collective Bias 29/05/2025

LLM Generated Persona is a Promise with a Catch 29/05/2025

Large Language Models for Digital Twin Simulation 29/05/2025

From RL Distillation to Autonomous LLM Agents 29/05/2025

Prompting, Auto-Prompting, and Human-AI Communication 29/05/2025

Textual Gradients for LLM Optimization 29/05/2025

Large Language Models as Markov Chains 28/05/2025

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation 28/05/2025

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