Papers by Prashant Bannulmath

1 papers
LaRA: Large Rank Adaptation for Speech and Text Cross-Modal Learning in Large Language Models (2024.findings-emnlp)

Copied to clipboard

Challenge: Existing approaches to integrate speech and text capabilities into large language models (LLMs) require significantly larger ranks comparable to the pretrained weights to accommodate the complexities of speech-text cross-modality learning.
Approach: They propose a large-rank adaptive approach for cross-modal integration of speech and text into large language models (LLMs) it uses a Hi-Fi vocoder to synthesize speech waveforms from the generated speech units.
Outcome: The proposed model can be extended to other cross-modal applications.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations