3 papers
cs.CL2025
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
NVIDIA, :, Aarti Basant +214
We introduce Nemotron-Nano-9B-v2, a hybrid Mamba-Transformer language model designed to increase throughput for reasoning workloads while achieving state-of-the-art accuracy compar…
cs.CL2025
SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling
Krishna C. Puvvada, Faisal Ladhak, Santiago Akle Serrano +8
We present a decoder-only Transformer architecture that robustly generalizes to sequence lengths substantially longer than those seen during training. Our model, SWAN-GPT, interlea…
eess.AS2023
Investigating End-to-End ASR Architectures for Long Form Audio Transcription
Nithin Rao Koluguri, Samuel Kriman, Georgy Zelenfroind +5
This paper presents an overview and evaluation of some of the end-to-end ASR models on long-form audios. We study three categories of Automatic Speech Recognition(ASR) models based…