33 citations · 37 across the 5 of their papers we have counts for
5 papers
Token-wise Curriculum Learning for Neural Machine Translation
Chen Liang, Haoming Jiang, Xiaodong Liu +4
Existing curriculum learning approaches to Neural Machine Translation (NMT) require sampling sufficient amounts of "easy" samples from training data at the early training stage. Th…
Greedy-Step Off-Policy Reinforcement Learning
Yuhui Wang, Qingyuan Wu, Pengcheng He +1
Most of the policy evaluation algorithms are based on the theories of Bellman Expectation and Optimality Equation, which derive two popular approaches - Policy Iteration (PI) and V…
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…
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…
Generation-Augmented Retrieval for Open-domain Question Answering
Yuning Mao, Pengcheng He, Xiaodong Liu +4
We propose Generation-Augmented Retrieval (GAR) for answering open-domain questions, which augments a query through text generation of heuristically discovered relevant contexts wi…