Best AI papers explained

A podcast by Enoch H. Kang

508 Episodio

Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision
Pubblicato: 27/09/2025
Learning without training: The implicit dynamics of in-context learning
Pubblicato: 24/09/2025
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model
Pubblicato: 24/09/2025
Open Problems in Mechanistic Interpretability
Pubblicato: 21/09/2025
Maestro: Joint Graph & Config Optimization for Reliable AI Agents
Pubblicato: 21/09/2025
Thought Anchors: Which LLM Reasoning Steps Matter?
Pubblicato: 21/09/2025
Sample Complexity and Representation Ability of Test-time Scaling Paradigms
Pubblicato: 09/09/2025
RL's Razor: Why Online RL Forgets Less
Pubblicato: 07/09/2025
Why Language Models Hallucinate
Pubblicato: 06/09/2025
ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning
Pubblicato: 06/09/2025
Sample Efficient Preference Alignment in LLMs via Active Exploration
Pubblicato: 06/09/2025
Adventures in Demand Analysis Using AI
Pubblicato: 04/09/2025
Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
Pubblicato: 01/09/2025
On the Theoretical Limitations of Embedding-Based Retrieval
Pubblicato: 31/08/2025
Performance Prediction for Large Systems via Text-to-Text Regression
Pubblicato: 30/08/2025
Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Pubblicato: 30/08/2025
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Pubblicato: 30/08/2025
Compute-Optimal Scaling for Value-Based Deep RL
Pubblicato: 25/08/2025
LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience
Pubblicato: 23/08/2025
Signal and Noise: Evaluating Language Model Benchmarks
Pubblicato: 23/08/2025

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508 Episodio

Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision

Learning without training: The implicit dynamics of in-context learning

Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model

Open Problems in Mechanistic Interpretability

Maestro: Joint Graph & Config Optimization for Reliable AI Agents

Thought Anchors: Which LLM Reasoning Steps Matter?

Sample Complexity and Representation Ability of Test-time Scaling Paradigms

RL's Razor: Why Online RL Forgets Less

Why Language Models Hallucinate

ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning

Sample Efficient Preference Alignment in LLMs via Active Exploration

Adventures in Demand Analysis Using AI

Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

On the Theoretical Limitations of Embedding-Based Retrieval

Performance Prediction for Large Systems via Text-to-Text Regression

Demystifying the Visual Quality Paradox in Multimodal Large Language Models

Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL

Compute-Optimal Scaling for Value-Based Deep RL

LLM-based Conversational Recommendation Agents with Collaborative Verbalized Experience

Signal and Noise: Evaluating Language Model Benchmarks