3 citations · 3 across the 4 of their papers we have counts for
4 papers
Gemma 4 Technical Report
Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…
StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel
Dylan Cutler, Arun Kandoor, Nishanth Dikkala +3
Decoding in a Transformer based language model is inherently sequential as a token's embedding needs to pass through all the layers in the network before the generation of the next…
Scalable Multi-Domain Adaptation of Language Models using Modular Experts
Peter Schafhalter, Shun Liao, Yanqi Zhou +3
Domain-specific adaptation is critical to maximizing the performance of pre-trained language models (PLMs) on one or multiple targeted tasks, especially under resource-constrained…
Tiny Neural Models for Seq2Seq
Arun Kandoor
Semantic parsing models with applications in task oriented dialog systems require efficient sequence to sequence (seq2seq) architectures to be run on-device. To this end, we propos…