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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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Adaptive Polyhedral Methods for Conjoint Analysis 11/04/2025

MSL: Enhancing LLM Recommenders via Masked Softmax Loss 11/04/2025

Self-Supervised Deep Reinforcement Learning for Optimal Question Ranking 11/04/2025

Adaptive Language Elicitation for Latent Information Discovery 10/04/2025

LLM Persona Bias: Promise and Peril in Simulation 10/04/2025

AutoTools: Automating Tool Use for Large Language Models 10/04/2025

Tool Learning with Large Language Models: A Comprehensive Survey 10/04/2025

All Roads Lead to Likelihood: RL for Fine-Tuning Value 08/04/2025

ATLAS: Tuning Agents via Critical Step Learning 08/04/2025

Thinking Faster by Writing Less: Chain of Draft Reasoning 08/04/2025

Meta Plan Optimization for Boosting LLM Agents 08/04/2025

L1: Length Controlled Reasoning with Reinforcement Learning 08/04/2025

WikiBigEdit: Benchmarking Lifelong Knowledge Editing in LLMs 08/04/2025

PLAN-AND-ACT: LLM Agent Planning with Synthetic Data 08/04/2025

SEARCH-R1: LLMs Learn to Reason and Search via Reinforcement Learning 08/04/2025

The Theory of the Firm: Information, Incentives, and Organization 08/04/2025

Four Formalizable Theories of the Firm 08/04/2025

Efficient Tool Use with Chain-of-Abstraction Reasoning 06/04/2025

CodeTool: Process Supervision for Enhanced LLM Tool Invocation 06/04/2025

Evaluating LLM Agents in Multi-Turn Conversations: A Survey 06/04/2025

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