Best AI papers explained

A podcast by Enoch H. Kang

550 Episodio

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models
Pubblicato: 27/05/2025
Improved Techniques for Training Score-Based Generative Models
Pubblicato: 27/05/2025
Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator
Pubblicato: 27/05/2025
AlphaEvolve: A coding agent for scientific and algorithmic discovery
Pubblicato: 27/05/2025
Harnessing the Universal Geometry of Embeddings
Pubblicato: 27/05/2025
Goal Inference using Reward-Producing Programs in a Novel Physics Environment
Pubblicato: 27/05/2025
Trial-Error-Explain In-Context Learning for Personalized Text Generation
Pubblicato: 27/05/2025
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Pubblicato: 27/05/2025
Test-Time Reinforcement Learning (TTRL)
Pubblicato: 27/05/2025
Interpreting Emergent Planning in Model-Free Reinforcement Learning
Pubblicato: 26/05/2025
Agentic Reward Modeling_Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
Pubblicato: 26/05/2025
Beyond Reward Hacking: Causal Rewards for Large LanguageModel Alignment
Pubblicato: 26/05/2025
Learning How Hard to Think: Input-Adaptive Allocation of LM Computation
Pubblicato: 26/05/2025
Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval
Pubblicato: 26/05/2025
UFT: Unifying Supervised and Reinforcement Fine-Tuning
Pubblicato: 26/05/2025
Understanding High-Dimensional Bayesian Optimization
Pubblicato: 26/05/2025
Inference time alignment in continuous space
Pubblicato: 25/05/2025
Efficient Test-Time Scaling via Self-Calibration
Pubblicato: 25/05/2025
Conformal Prediction via Bayesian Quadrature
Pubblicato: 25/05/2025
Predicting from Strings: Language Model Embeddings for Bayesian Optimization
Pubblicato: 25/05/2025

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550 Episodio

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models

Improved Techniques for Training Score-Based Generative Models

Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator

AlphaEvolve: A coding agent for scientific and algorithmic discovery

Harnessing the Universal Geometry of Embeddings

Goal Inference using Reward-Producing Programs in a Novel Physics Environment

Trial-Error-Explain In-Context Learning for Personalized Text Generation

Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Test-Time Reinforcement Learning (TTRL)

Interpreting Emergent Planning in Model-Free Reinforcement Learning

Agentic Reward Modeling_Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems

Beyond Reward Hacking: Causal Rewards for Large LanguageModel Alignment

Learning How Hard to Think: Input-Adaptive Allocation of LM Computation

Highlighting What Matters: Promptable Embeddings for Attribute-Focused Image Retrieval

UFT: Unifying Supervised and Reinforcement Fine-Tuning

Understanding High-Dimensional Bayesian Optimization

Inference time alignment in continuous space

Efficient Test-Time Scaling via Self-Calibration

Conformal Prediction via Bayesian Quadrature

Predicting from Strings: Language Model Embeddings for Bayesian Optimization