188 citations · 189 across the 5 of their papers we have counts for
8 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
ExecuTorch -- A Unified PyTorch Solution to Run AI Models On-Device
Mergen Nachin, Digant Desai, Sicheng Stephen Jia +36
Local execution of AI on edge devices is important for low latency and offline operation. However, deploying models on diverse hardware remains fragmented, often requiring model co…
Using Machine Translation to Localize Task Oriented NLG Output
Scott Roy, Cliff Brunk, Kyu-Young Kim +6
One of the challenges in a task oriented natural language application like the Google Assistant, Siri, or Alexa is to localize the output to many languages. This paper explores doi…
Machine Translation Pre-training for Data-to-Text Generation -- A Case Study in Czech
Mihir Kale, Scott Roy
While there is a large body of research studying deep learning methods for text generation from structured data, almost all of it focuses purely on English. In this paper, we study…
APE at Scale and its Implications on MT Evaluation Biases
Markus Freitag, Isaac Caswell, Scott Roy
In this work, we train an Automatic Post-Editing (APE) model and use it to reveal biases in standard Machine Translation (MT) evaluation procedures. The goal of our APE model is to…
Unsupervised Natural Language Generation with Denoising Autoencoders
Markus Freitag, Scott Roy
Generating text from structured data is important for various tasks such as question answering and dialog systems. We show that in at least one domain, without any supervision and…
Contextual LSTM (CLSTM) models for Large scale NLP tasks
Shalini Ghosh, Oriol Vinyals, Brian Strope +3
Documents exhibit sequential structure at multiple levels of abstraction (e.g., sentences, paragraphs, sections). These abstractions constitute a natural hierarchy for representing…
Hierarchical Composable Optimization of Web Pages
Ronen Barenboim, Edward Bortnikov, Nadav Golbandi +6
The process of creating modern Web media experiences is challenged by the need to adapt the content and presentation choices to dynamic real-time fluctuations of user interest acro…