Best AI papers explained
A podcast by Enoch H. Kang
550 Episodio
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PLAN-AND-ACT: LLM Agent Planning with Synthetic Data
Pubblicato: 08/04/2025 -
SEARCH-R1: LLMs Learn to Reason and Search via Reinforcement Learning
Pubblicato: 08/04/2025 -
The Theory of the Firm: Information, Incentives, and Organization
Pubblicato: 08/04/2025 -
Four Formalizable Theories of the Firm
Pubblicato: 08/04/2025 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Pubblicato: 06/04/2025 -
CodeTool: Process Supervision for Enhanced LLM Tool Invocation
Pubblicato: 06/04/2025 -
Evaluating LLM Agents in Multi-Turn Conversations: A Survey
Pubblicato: 06/04/2025 -
Epistemic Alignment in User-LLM Knowledge Delivery
Pubblicato: 06/04/2025 -
MCP is (not) all you need
Pubblicato: 06/04/2025 -
AI, Human Skills, and Competitive Advantage in Chess
Pubblicato: 05/04/2025 -
Inference-Time Scaling for Generalist Reward Modeling
Pubblicato: 04/04/2025 -
Optimal Pure Exploration in Linear Bandits via Sampling
Pubblicato: 04/04/2025 -
Presidential Address: The Economist as Designer in the Innovation Process for Socially Impactful Digital Products
Pubblicato: 04/04/2025 -
Emergent Symbolic Mechanisms for Reasoning in Large Language Models
Pubblicato: 03/04/2025 -
Inference-Time Alignment: Coverage, Scaling, and Optimality
Pubblicato: 03/04/2025 -
Sharpe Ratio-Guided Active Learning for Preference Optimization
Pubblicato: 03/04/2025 -
Active Learning for Adaptive In-Context Prompt Design
Pubblicato: 03/04/2025 -
Visual Chain-of-Thought Reasoning for Vision-Language-Action Models
Pubblicato: 03/04/2025 -
On the Biology of a Large Language Model
Pubblicato: 01/04/2025 -
Async-TB: Asynchronous Trajectory Balance for Scalable LLM RL
Pubblicato: 01/04/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
