16 citations · 60 across the 78 of their papers we have counts for
7 papers · 1 filter
TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription
Akshaj Gupta, Hwi Joo Park, Andrea Guzman +5
Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as slides, bends, and percussi…
Asymmetric Hierarchical Anchoring for Robust Audio-Visual Cross-Modal Generalization
Bixing Wu, Yuhong Zhao, Zongli Ye +3
Audio-visual joint representation learning under Cross-Modal Generalization (CMG) aims to transfer knowledge from a labeled source modality to an unlabeled target modality through…
Evolutionary Strategies lead to Catastrophic Forgetting in LLMs
Immanuel Abdi, Akshat Gupta, Micah Mok +3
One of the biggest missing capabilities in current AI systems is the ability to learn continuously after deployment. Implementing such continually learning systems have several cha…
Geometric Interpretation of Layer Normalization and a Comparative Analysis with RMSNorm
Akshat Gupta, Atahan Ozdemir, Gopala Anumanchipalli
This paper presents a novel geometric interpretation of LayerNorm and explores how LayerNorm influences the norm and orientation of hidden vectors in the representation space. With…
A Unified Framework for Model Editing
Akshat Gupta, Dev Sajnani, Gopala Anumanchipalli
ROME and MEMIT are largely believed to be two different model editing algorithms, with the major difference between them being the ability to perform batched edits. In this paper,…
Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data
Cheol Jun Cho, Edward F. Chang, Gopala K. Anumanchipalli
Understanding the neural implementation of complex human behaviors is one of the major goals in neuroscience. To this end, it is crucial to find a true representation of the neural…
Brain2Char: A Deep Architecture for Decoding Text from Brain Recordings
Pengfei Sun, Gopala K. Anumanchipalli, Edward F. Chang
Decoding language representations directly from the brain can enable new Brain-Computer Interfaces (BCI) for high bandwidth human-human and human-machine communication. Clinically,…