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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.

619 episodios disponibles

Latest episodes of the podcast Best AI papers explained

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Optimal Pure Exploration in Linear Bandits via Sampling 04/04/2025

Presidential Address: The Economist as Designer in the Innovation Process for Socially Impactful Digital Products 04/04/2025

Emergent Symbolic Mechanisms for Reasoning in Large Language Models 03/04/2025

Inference-Time Alignment: Coverage, Scaling, and Optimality 03/04/2025

Sharpe Ratio-Guided Active Learning for Preference Optimization 03/04/2025

Active Learning for Adaptive In-Context Prompt Design 03/04/2025

Visual Chain-of-Thought Reasoning for Vision-Language-Action Models 03/04/2025

On the Biology of a Large Language Model 01/04/2025

Async-TB: Asynchronous Trajectory Balance for Scalable LLM RL 01/04/2025

Instacart's Economics Team: A Hybrid Role in Tech 31/03/2025

Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework 31/03/2025

Why MCP won 31/03/2025

SWEET-RL: Training LLM Agents for Collaborative Reasoning 31/03/2025

TheoryCoder: Bilevel Planning with Synthesized World Models 30/03/2025

Driving Forces in AI: Scaling to 2025 and Beyond (Jason Wei, OpenAI) 29/03/2025

Expert Demonstrations for Sequential Decision Making under Heterogeneity 28/03/2025

TextGrad: Backpropagating Language Model Feedback for Generative AI Optimization 27/03/2025

MemReasoner: Generalizing Language Models on Reasoning-in-a-Haystack Tasks 27/03/2025

RAFT: In-Domain Retrieval-Augmented Fine-Tuning for Language Models 27/03/2025

Inductive Biases for Exchangeable Sequence Modeling 26/03/2025

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