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Communicating Sound Through Natural Language
Natural language is widely used to describe, prompt, and control audio systems, but rarely serves as the representation carrying audio …
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Communicating Sound Through Natural Language
Multi-objective Evolutionary Merging Enables Efficient Reasoning Models
Reasoning models have demonstrated remarkable capabilities in solving complex problems by leveraging long chains of thought. However, …
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Multi-objective Evolutionary Merging Enables Efficient Reasoning Models
Zero-Shot Quantization via Weight-Space Arithmetic
We show that robustness to post-training quantization (PTQ) is a transferable direction in weight space. We call this direction the …
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Zero-Shot Quantization via Weight-Space Arithmetic
Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data
Nonrigid registration is conventionally divided into point set registration, which aligns sparse geometries, and image registration, …
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Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data
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 …
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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 …
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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 …
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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 …
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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 …
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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 …
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From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication