15 citations · 135 across the 41 of their papers we have counts for
Showing 2023 · cs.CLShow all
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cs.CL2023★ 3 cited
Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation
Changtong Zan, Liang Ding, Li Shen +4
Zero-shot translation (ZST), which is generally based on a multilingual neural machine translation model, aims to translate between unseen language pairs in training data. The comm…
cs.CL2023★ 1 cited
Divide, Conquer, and Combine: Mixture of Semantic-Independent Experts for Zero-Shot Dialogue State Tracking
Qingyue Wang, Liang Ding, Yanan Cao +5
Zero-shot transfer learning for Dialogue State Tracking (DST) helps to handle a variety of task-oriented dialogue domains without the cost of collecting in-domain data. Existing wo…
cs.CL2023★ 10 cited
Bag of Tricks for Effective Language Model Pretraining and Downstream Adaptation: A Case Study on GLUE
Qihuang Zhong, Liang Ding, Keqin Peng +5
This technical report briefly describes our JDExplore d-team's submission Vega v1 on the General Language Understanding Evaluation (GLUE) leaderboard, where GLUE is a collection of…