Search Results for author:
Found 7 papers, 2 papers with code
FAST: Factorizable Attention for Speeding up Transformers
Motivated by the factorization inherent in the original fast multipole method and the improved fast Gauss transform we introduce a factorable form of attention that operates efficiently in high dimensions.
A Closer Look at the Limitations of Instruction Tuning
Our findings reveal that responses generated solely from pre-trained knowledge consistently outperform responses by models that learn any form of new knowledge from IT on open-source datasets.
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
In this paper, we propose CompA, a collection of two expert-annotated benchmarks with a majority of real-world audio samples, to evaluate compositional reasoning in ALMs.
RECAP: Retrieval-Augmented Audio Captioning
We present RECAP (REtrieval-Augmented Audio CAPtioning), a novel and effective audio captioning system that generates captions conditioned on an input audio and other captions similar to the audio retrieved from a datastore.
Gaussian Process Models for HRTF based Sound-Source Localization and Active-Learning
From a machine learning perspective, the human ability localize sounds can be modeled as a non-parametric and non-linear regression problem between binaural spectral features of sound received at the ears (input) and their sound-source directions (output).
Software for Computing the Spheroidal Wave Functions Using Arbitrary Precision Arithmetic
The spheroidal wave functions, which are the solutions to the Helmholtz equation in spheroidal coordinates, are notoriously difficult to compute.
Mathematical Software Numerical Analysis
Automatic online tuning for fast Gaussian summation
To solve the second problem, we present an online tuning approach that results in a black box method that automatically chooses the evaluation method and its parameters to yield the best performance for the input data, desired accuracy, and bandwidth.
