14 citations · 20 across the 12 of their papers we have counts for
5 papers · 1 filter
M*: A Modular, Extensible, Serving System for Multimodal Models
Atindra Jha, Naomi Sagan, Keisuke Kamahori +9
We are entering a new era of composite model architectures that integrate diverse components such as vision encoders, language backbones, diffusion and flow heads, audio codecs, ac…
MURMUR: An Efficient Inference System for Long-Form ASR
Wei-Tzu Lee, Keisuke Kamahori, Baris Kasikci
Long-form automatic speech recognition (ASR) requires both high accuracy and low latency, but existing systems force a trade-off between the two. Chunk-based pipelines process audi…
VoxServe: Streaming-Centric Serving System for Speech Language Models
Keisuke Kamahori, Wei-Tzu Lee, Atindra Jha +4
Deploying modern Speech Language Models (SpeechLMs) in streaming settings requires systems that provide low latency, high throughput, and strong guarantees of streamability. Existi…
LiteASR: Efficient Automatic Speech Recognition with Low-Rank Approximation
Keisuke Kamahori, Jungo Kasai, Noriyuki Kojima +1
Modern automatic speech recognition (ASR) models, such as OpenAI's Whisper, rely on deep encoder-decoder architectures, and their encoders are a critical bottleneck for efficient d…
Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models
Keisuke Kamahori, Tian Tang, Yile Gu +2
Large Language Models (LLMs) with the Mixture-of-Experts (MoE) architectures have shown promising performance on various tasks. However, due to the huge model sizes, running them i…