Best AI papers explained

Podcast készítő Enoch H. Kang

550 Epizód

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

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550 Epizód

DoubleGen - Debiased Generative Modeling of Counterfactuals

What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT

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