5.7k citations · 8.2k across the 48 of their papers we have counts for
8 papers · 1 filter
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed, Zheng Xu, Ankush Garg +2
Federated learning is used for decentralized training of machine learning models on a large number (millions) of edge mobile devices. It is challenging because mobile devices often…
Understanding How Encoder-Decoder Architectures Attend
Kyle Aitken, Vinay V Ramasesh, Yuan Cao +1
Encoder-decoder networks with attention have proven to be a powerful way to solve many sequence-to-sequence tasks. In these networks, attention aligns encoder and decoder states an…
SGD-X: A Benchmark for Robust Generalization in Schema-Guided Dialogue Systems
Harrison Lee, Raghav Gupta, Abhinav Rastogi +3
Zero/few-shot transfer to unseen services is a critical challenge in task-oriented dialogue research. The Schema-Guided Dialogue (SGD) dataset introduced a paradigm for enabling mo…
Towards Zero-Label Language Learning
Zirui Wang, Adams Wei Yu, Orhan Firat +1
This paper explores zero-label learning in Natural Language Processing (NLP), whereby no human-annotated data is used anywhere during training and models are trained purely on synt…
Effective Sequence-to-Sequence Dialogue State Tracking
Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang +2
Sequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In…
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
Zirui Wang, Jiahui Yu, Adams Wei Yu +3
With recent progress in joint modeling of visual and textual representations, Vision-Language Pretraining (VLP) has achieved impressive performance on many multimodal downstream ta…
Improving Longer-range Dialogue State Tracking
Ye Zhang, Yuan Cao, Mahdis Mahdieh +2
Dialogue state tracking (DST) is a pivotal component in task-oriented dialogue systems. While it is relatively easy for a DST model to capture belief states in short conversations,…
Echo State Speech Recognition
Harsh Shrivastava, Ankush Garg, Yuan Cao +2
We propose automatic speech recognition (ASR) models inspired by echo state network (ESN), in which a subset of recurrent neural networks (RNN) layers in the models are randomly in…