3

Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. While recent work …
Cite arXiv
Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
Multi-Way Representation Alignment
The Platonic Representation Hypothesis suggests that independently trained neural networks converge to increasingly similar latent …
Cite arXiv
Multi-Way Representation Alignment
Activation Patching for Interpretable Steering in Music Generation
Understanding how large audio models represent music, and using that understanding to steer generation, is both challenging and …
Cite arXiv
Activation Patching for Interpretable Steering in Music Generation
Decoding RNA-RNA Interactions: The Role of Low-Complexity Repeats and a Deep Learning Framework for Sequence-Based Prediction
RNA-RNA interactions (RRIs) are fundamental to gene regulation and RNA processing, yet their molecular determinants remain unclear. In …
Cite bioRxiv GitHub
Decoding RNA-RNA Interactions: The Role of Low-Complexity Repeats and a Deep Learning Framework for Sequence-Based Prediction
COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations
We present COCOLA (Coherence-Oriented Contrastive Learning for Audio), a contrastive learning method for musical audio representations …
Cite arXiv GitHub
COCOLA: Coherence-Oriented Contrastive Learning of Musical Audio Representations
ATM: Improving Model Merging by Alternating Tuning and Merging
Model merging has recently emerged as a cost-efficient paradigm for multi-task learning. Among current approaches, task arithmetic …
Cite arXiv GitHub
ATM: Improving Model Merging by Alternating Tuning and Merging
Latent Space Translation via Inverse Relative Projection
The emergence of similar representations between independently trained neural models has sparked significant interest in the …
Cite arXiv
Latent Space Translation via Inverse Relative Projection
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
It has been observed that representations learned by distinct neural networks conceal structural similarities when the models are …
Cite PDF URL ICLR 2024 spotlight
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splatting
We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of …
Cite arXiv
GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splatting
Zero-Shot Duet Singing Voices Separation with Diffusion Models
In recent studies, diffusion models have shown promise as priors for solving audio inverse problems, including source separation. These …
Cite PDF arXiv GitHub
Zero-Shot Duet Singing Voices Separation with Diffusion Models