Generalizing Reward Modeling for Out-of-Distribution Preference Learning
Preference learning aims to align the generations of large language models (LLMs) with human preferences. Most previous…
Rao-Blackwellising Bayesian Causal Inference
The authors propose a new method for Bayesian causal inference, combining order-based MCMC structure learning with gradient-based…
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
The paper introduces Self-guided Masked Autoencoders (SMA), a method for self-supervised learning that works without domain-specific assumptions….
Link Prediction under Heterophily: A Physics-Inspired Graph Neural Network Approach
The article presents a study on the use of Graph Neural Networks (GNNs) for link prediction in…
Difference Learning for Air Quality Forecasting Transport Emulation
The article discusses the development of a deep learning transport emulator to improve air quality forecasting. It…
When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection
Depression is a major global mental health concern. To address this, the paper presents a method for…
Voice-Driven Mortality Prediction in Hospitalized Heart Failure Patients: A Machine Learning Approach Enhanced with Diagnostic Biomarkers
The article presents a machine learning model designed to predict mortality rates in heart failure patients using…
Structure-informed Positional Encoding for Music Generation
The paper proposes a new structure-informed positional encoding framework for music generation with Transformers. The authors note…
The Effect of Batch Size on Contrastive Self-Supervised Speech Representation Learning
The article focuses on the impact of batch size on pre-training in self-supervised speech representation learning. The…
Music Style Transfer with Time-Varying Inversion of Diffusion Models
This paper presents a new approach for music style transfer using diffusion models. This approach effectively captures…