2 citations · 5 across the 12 of their papers we have counts for
4 papers · 1 filter
Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM
Ryan Solgi, Parsa Madinei, Jiayi Tian +4
Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and computing challenges in deployment.…
Saten: Sparse Augmented Tensor Networks for Post-Training Compression of Large Language Models
Ryan Solgi, Kai Zhen, Rupak Vignesh Swaminathan +4
The efficient implementation of large language models (LLMs) is crucial for deployment on resource-constrained devices. Low-rank tensor compression techniques, such as tensor-train…
A neural prosody encoder for end-ro-end dialogue act classification
Kai Wei, Dillon Knox, Martin Radfar +6
Dialogue act classification (DAC) is a critical task for spoken language understanding in dialogue systems. Prosodic features such as energy and pitch have been shown to be useful…
Attentive Contextual Carryover for Multi-Turn End-to-End Spoken Language Understanding
Kai Wei, Thanh Tran, Feng-Ju Chang +8
Recent years have seen significant advances in end-to-end (E2E) spoken language understanding (SLU) systems, which directly predict intents and slots from spoken audio. While dialo…