Best AI papers explained
Un pódcast de Enoch H. Kang
518 Episodo
-  The Agentic EconomyPublicado: 30/5/2025
-  Statistics for Large Language ModelsPublicado: 29/5/2025
-  Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based SearchPublicado: 29/5/2025
-  Beyond Markovian: Reflective Exploration via Bayes-Adaptive RL for LLM ReasoningPublicado: 29/5/2025
-  Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RLPublicado: 29/5/2025
-  Value-Guided Search for Efficient Chain-of-Thought ReasoningPublicado: 29/5/2025
-  Shallow Preference Signals: Large Language model aligns even better without truncated data?Publicado: 29/5/2025
-  Gaming Tool Preferences in Agentic LLMsPublicado: 29/5/2025
-  Partner Modelling Emerges in Recurrent Agents (But Only When It Matters)Publicado: 29/5/2025
-  LLM Populations Form Social Conventions and Collective BiasPublicado: 29/5/2025
-  LLM Generated Persona is a Promise with a CatchPublicado: 29/5/2025
-  Large Language Models for Digital Twin SimulationPublicado: 29/5/2025
-  From RL Distillation to Autonomous LLM AgentsPublicado: 29/5/2025
-  Prompting, Auto-Prompting, and Human-AI CommunicationPublicado: 29/5/2025
-  Textual Gradients for LLM OptimizationPublicado: 29/5/2025
-  Large Language Models as Markov ChainsPublicado: 28/5/2025
-  Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and DistillationPublicado: 28/5/2025
-  Selective induction heads: how transformers select causal structures in contextPublicado: 28/5/2025
-  The Evolution of Statistical Induction Heads: In-Context Learning Markov ChainsPublicado: 28/5/2025
-  How Transformers Learn Causal Structure with Gradient DescentPublicado: 28/5/2025
Cut through the noise. We curate and break down the most important AI papers so you don’t have to.
