activity
20172021
most citedUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training

225 citations · 325 across the 6 of their papers we have counts for

collaborators

18 papers

cs.CL20216 cited

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding

Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng +6

Most recent progress in natural language understanding (NLU) has been driven, in part, by benchmarks such as GLUE, SuperGLUE, SQuAD, etc. In fact, many NLU models have now matched…

cs.CL2021

Rider: Reader-Guided Passage Reranking for Open-Domain Question Answering

Yuning Mao, Pengcheng He, Xiaodong Liu +4

Current open-domain question answering systems often follow a Retriever-Reader architecture, where the retriever first retrieves relevant passages and the reader then reads the ret…

cs.CL2021

UnitedQA: A Hybrid Approach for Open Domain Question Answering

Hao Cheng, Yelong Shen, Xiaodong Liu +3

To date, most of recent work under the retrieval-reader framework for open-domain QA focuses on either extractive or generative reader exclusively. In this paper, we study a hybrid…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…

cs.CL2020

A Tale of Two Linkings: Dynamically Gating between Schema Linking and Structural Linking for Text-to-SQL Parsing

Sanxing Chen, Aidan San, Xiaodong Liu +1

In Text-to-SQL semantic parsing, selecting the correct entities (tables and columns) for the generated SQL query is both crucial and challenging; the parser is required to connect…

cs.CL2020

Very Deep Transformers for Neural Machine Translation

Xiaodong Liu, Kevin Duh, Liyuan Liu +1

We explore the application of very deep Transformer models for Neural Machine Translation (NMT). Using a simple yet effective initialization technique that stabilizes training, we…