Best AI papers explained

Podcast készítő Enoch H. Kang

550 Epizód

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models
Közzétéve: 2025. 06. 07.
Decisions With Algorithms
Közzétéve: 2025. 06. 07.
Adapting, fast and slow: Causal Approach to Few-Shot Sequence Learning
Közzétéve: 2025. 06. 06.
Conformal Arbitrage for LLM Objective Balancing
Közzétéve: 2025. 06. 06.
Simulation-Based Inference for Adaptive Experiments
Közzétéve: 2025. 06. 06.
Agents as Tool-Use Decision-Makers
Közzétéve: 2025. 06. 06.
Quantitative Judges for Large Language Models
Közzétéve: 2025. 06. 06.
Self-Challenging Language Model Agents
Közzétéve: 2025. 06. 06.
Learning to Explore: An In-Context Learning Approach for Pure Exploration
Közzétéve: 2025. 06. 06.
How Bidirectionality Helps Language Models Learn Better via Dynamic Bottleneck Estimation
Közzétéve: 2025. 06. 06.
A Closer Look at Bias and Chain-of-Thought Faithfulness of Large (Vision) Language Models
Közzétéve: 2025. 06. 05.
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Közzétéve: 2025. 06. 05.
Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models
Közzétéve: 2025. 06. 05.
IPO: Interpretable Prompt Optimization for Vision-Language Models
Közzétéve: 2025. 06. 05.
Evolutionary Prompt Optimization discovers emergent multimodal reasoning strategies
Közzétéve: 2025. 06. 05.
Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know?
Közzétéve: 2025. 06. 04.
Diffusion Guidance Is a Controllable Policy Improvement Operator
Közzétéve: 2025. 06. 02.
Alita: Generalist Agent With Self-Evolution
Közzétéve: 2025. 06. 02.
A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning
Közzétéve: 2025. 06. 02.
Learning Compositional Functions with Transformers from Easy-to-Hard Data
Közzétéve: 2025. 06. 02.

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550 Epizód

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models

Decisions With Algorithms

Adapting, fast and slow: Causal Approach to Few-Shot Sequence Learning

Conformal Arbitrage for LLM Objective Balancing

Simulation-Based Inference for Adaptive Experiments

Agents as Tool-Use Decision-Makers

Quantitative Judges for Large Language Models

Self-Challenging Language Model Agents

Learning to Explore: An In-Context Learning Approach for Pure Exploration

How Bidirectionality Helps Language Models Learn Better via Dynamic Bottleneck Estimation

A Closer Look at Bias and Chain-of-Thought Faithfulness of Large (Vision) Language Models

Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling

Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models

IPO: Interpretable Prompt Optimization for Vision-Language Models

Evolutionary Prompt Optimization discovers emergent multimodal reasoning strategies

Evaluating the Unseen Capabilities: How Many Theorems Do LLMs Know?

Diffusion Guidance Is a Controllable Policy Improvement Operator

Alita: Generalist Agent With Self-Evolution

A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning

Learning Compositional Functions with Transformers from Easy-to-Hard Data