24 citations · 50 across the 10 of their papers we have counts for
10 papers
Now It Sounds Like You: Learning Personalized Vocabulary On Device
Sid Wang, Ashish Shenoy, Pierce Chuang +1
In recent years, Federated Learning (FL) has shown significant advancements in its ability to perform various natural language processing (NLP) tasks. This work focuses on applying…
BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation
Eleftheria Briakou, Sida I. Wang, Luke Zettlemoyer +1
Mined bitexts can contain imperfect translations that yield unreliable training signals for Neural Machine Translation (NMT). While filtering such pairs out is known to improve fin…
SILG: The Multi-environment Symbolic Interactive Language Grounding Benchmark
Victor Zhong, Austin W. Hanjie, Sida I. Wang +2
Existing work in language grounding typically study single environments. How do we build unified models that apply across multiple environments? We propose the multi-environment Sy…
Deep Natural Language Processing for LinkedIn Search
Weiwei Guo, Xiaowei Liu, Sida Wang +7
Many search systems work with large amounts of natural language data, e.g., search queries, user profiles, and documents. Building a successful search system requires a thorough un…
Deep Natural Language Processing for LinkedIn Search Systems
Weiwei Guo, Xiaowei Liu, Sida Wang +6
Many search systems work with large amounts of natural language data, e.g., search queries, user profiles and documents, where deep learning based natural language processing techn…
Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms
Yilun Zhou, Adithya Renduchintala, Xian Li +3
Active learning (AL) algorithms may achieve better performance with fewer data because the model guides the data selection process. While many algorithms have been proposed, there…