Categories: FAANG

Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection

Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-training multimodal LLMs is challenging. To this end, we propose a Fusion Low Rank Adaptation (FLoRA) technique that efficiently adapts a pre-trained unimodal LLM to consume new, previously unseen modalities via low rank adaptation. For device-directed speech detection, using FLoRA, the multimodal LLM achieves 22% relative reduction in equal error rate (EER) over…
AI Generated Robotic Content

Recent Posts

Best guess as to which tools were used for this? VACE v2v?

credit to @ unreelinc submitted by /u/Leading_Primary_8447 [link] [comments]

7 hours ago

Calculating What Your Bank Spends on Marketing Compliance Reviews

By Taylor Mahoney, VP of Solutions ConsultingPicture this. The Federal Reserve has just dropped interest…

7 hours ago

AlphaGenome: AI for better understanding the genome

Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to…

7 hours ago

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining

This paper was accepted to the ACL 2025 main conference as an oral presentation. This…

7 hours ago

Build an intelligent multi-agent business expert using Amazon Bedrock

In this post, we demonstrate how to build a multi-agent system using multi-agent collaboration in…

7 hours ago

How Schroders built its multi-agent financial analysis research assistant

Financial analysts spend hours grappling with ever-increasing volumes of market and company data to extract…

7 hours ago