Latest Articles for Generalization

This study investigates how language models grasp uncommon grammar structures.

This study explores how robots learn language and actions through experiences.

This article examines the difficulties of adapting deep learning in dynamic environments.

Study investigates how near-interpolating models perform on unseen data.

Exploring how transformers favor low sensitivity functions for improved performance.

Introducing Smart, a method for better GNN performance in changing graphs.

A look at tackling stereotypes in technology through language models.

A study on enhancing few-shot learning through effective backbone training techniques.

List learning allows computers to provide multiple answers, improving accuracy in AI systems.

New tools enhance online shopping by improving product search efficiency.

Examining how quantization can improve neural network performance and generalization.

Teaching robots tasks through simple demonstrations shows great potential for adaptability.

A new system improves realistic gesture creation using only speech audio.

New framework leverages large language models for understanding 3D scenes from images.

Discover how sleep impacts motor skill learning and retention.

This article discusses how transformers learn language structure through training methods.

A new approach to enhance deep learning models against adversarial attacks.

A look at how IRM improves machine learning generalization across different environments.

Enhancing State Space Models through better training techniques for time series data.

Examining traffic patterns using pooled data for better urban management.

Introducing sharpness-aware minimization to improve feature construction in genetic programming.

A new method speeds up training of complex models.

New method improves neural networks' performance against adversarial attacks.

RobustMVS improves 3D reconstruction by enhancing model generalization.

Causal chambers provide real data for validating AI methods through controlled experiments.

Introducing a method for improved image matching across diverse visual data.

A look into factors influencing learning in machine learning models.

A study introduces RepNoise to protect large language models from harmful fine-tuning.

A model that effectively fills in missing values in time series data.

Discover how hypercomplex deep learning improves data processing and model performance.

Explore the role of memory and context in improving machine learning.

Explore how computer programs can be automatically generated to meet specific requirements.

A new driving world model tackles challenges in autonomous driving technology.

Exploring the role of gradient descent in stochastic optimization and its implications for sample size.

Poseidon uses machine learning to efficiently predict solutions for complex PDEs.

A new method for fine-tuning language models using self-attention.

Research shows diverse instructions improve language model performance in unseen tasks.

This study proposes a new approach to maintain learning in AI systems.

Introducing an innovative model to improve cardinality estimation accuracy in database queries.

This article examines how planning budgets affect DNC models in solving problems.