113 citations · 161 across the 6 of their papers we have counts for
4 papers · 1 filter
CALICO: Conversational Agent Localization via Synthetic Data Generation
Andy Rosenbaum, Pegah Kharazmi, Ershad Banijamali +8
We present CALICO, a method to fine-tune Large Language Models (LLMs) to localize conversational agent training data from one language to another. For slots (named entities), CALIC…
Low-Resource Compositional Semantic Parsing with Concept Pretraining
Subendhu Rongali, Mukund Sridhar, Haidar Khan +3
Semantic parsing plays a key role in digital voice assistants such as Alexa, Siri, and Google Assistant by mapping natural language to structured meaning representations. When we w…
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model
Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald +13
In this work, we demonstrate that multilingual large-scale sequence-to-sequence (seq2seq) models, pre-trained on a mixture of denoising and Causal Language Modeling (CLM) tasks, ar…
Multi-Perspective Context Matching for Machine Comprehension
Zhiguo Wang, Haitao Mi, Wael Hamza +1
Previous machine comprehension (MC) datasets are either too small to train end-to-end deep learning models, or not difficult enough to evaluate the ability of current MC techniques…