5 papers
DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone
Vaibhav Singh, Oleksiy Ostapenko, Pierre-André Noël +2
Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive (AR) generation, yet their reliance on Transformer backbones limits inference efficiency…
Apriel-H1: Towards Efficient Enterprise Reasoning Models
Oleksiy Ostapenko, Luke Kumar, Raymond Li +10
Large Language Models (LLMs) achieve remarkable reasoning capabilities through transformer architectures with attention mechanisms. However, transformers suffer from quadratic time…
Apriel-Nemotron-15B-Thinker
Shruthan Radhakrishna, Soham Parikh, Gopal Sarda +32
While large language models (LLMs) have achieved remarkable reasoning capabilities across domains like code, math and other enterprise tasks, their significant memory and computati…
Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training
Oleksiy Ostapenko, Charles Guille-Escuret, Luke Kumar +7
We introduce a framework for optimizing domain-specific dataset construction in foundation model training. Specifically, we seek a cost-efficient way to estimate the quality of dat…
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
Samin Yeasar Arnob, Zhan Su, Minseon Kim +6
Merging parameter-efficient task experts has recently gained growing attention as a way to build modular architectures that can be rapidly adapted on the fly for specific downstrea…