Best AI papers explained

Podcast tekijän mukaan Enoch H. Kang

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534 Jaksot

Inference time alignment in continuous space
Julkaistiin: 25.5.2025
Efficient Test-Time Scaling via Self-Calibration
Julkaistiin: 25.5.2025
Conformal Prediction via Bayesian Quadrature
Julkaistiin: 25.5.2025
Predicting from Strings: Language Model Embeddings for Bayesian Optimization
Julkaistiin: 25.5.2025
Self-Evolving Curriculum for LLM Reasoning
Julkaistiin: 25.5.2025
Online Decision-Focused Learning in Dynamic Environments
Julkaistiin: 25.5.2025
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Julkaistiin: 25.5.2025
Reward Shaping from Confounded Offline Data
Julkaistiin: 25.5.2025
Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning
Julkaistiin: 25.5.2025
Understanding Best-of-N Language Model Alignment
Julkaistiin: 25.5.2025
Maximizing Acquisition Functions for Bayesian Optimization - and its relation to Gradient Descent
Julkaistiin: 24.5.2025
Bayesian Prompt Ensembles: Model Uncertainty Estimation for Black-Box Large Language Models
Julkaistiin: 24.5.2025
Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation
Julkaistiin: 24.5.2025
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization
Julkaistiin: 24.5.2025
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
Julkaistiin: 24.5.2025
Automated Social Science: A Structural Causal Model-Based Approach
Julkaistiin: 24.5.2025
Causal Interpretation of Transformer Self-Attention
Julkaistiin: 24.5.2025
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Julkaistiin: 24.5.2025
Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs
Julkaistiin: 24.5.2025
Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation
Julkaistiin: 24.5.2025

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534 Jaksot

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

Self-Evolving Curriculum for LLM Reasoning

Online Decision-Focused Learning in Dynamic Environments

FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain

Reward Shaping from Confounded Offline Data

Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning

Understanding Best-of-N Language Model Alignment

Maximizing Acquisition Functions for Bayesian Optimization - and its relation to Gradient Descent

Bayesian Prompt Ensembles: Model Uncertainty Estimation for Black-Box Large Language Models

Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation

The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch

Automated Social Science: A Structural Causal Model-Based Approach

Causal Interpretation of Transformer Self-Attention

A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment

Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation