activity
20202022
most citedTemplate-Based Named Entity Recognition Using BART

11 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2022

Improved Data Augmentation for Translation Suggestion

Hongxiao Zhang, Siyu Lai, Songming Zhang +4

Translation suggestion (TS) models are used to automatically provide alternative suggestions for incorrect spans in sentences generated by machine translation. This paper introduce…

cs.CL2022

Conditional Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation

Songming Zhang, Yijin Liu, Fandong Meng +4

Token-level adaptive training approaches can alleviate the token imbalance problem and thus improve neural machine translation, through re-weighting the losses of different target…

cs.CL2021

Solving Aspect Category Sentiment Analysis as a Text Generation Task

Jian Liu, Zhiyang Teng, Leyang Cui +2

Aspect category sentiment analysis has attracted increasing research attention. The dominant methods make use of pre-trained language models by learning effective aspect category-s…

cs.CL202111 cited

Template-Based Named Entity Recognition Using BART

Leyang Cui, Yu Wu, Jian Liu +2

There is a recent interest in investigating few-shot NER, where the low-resource target domain has different label sets compared with a resource-rich source domain. Existing method…

cs.CL20204 cited

Natural Language Inference in Context -- Investigating Contextual Reasoning over Long Texts

Hanmeng Liu, Leyang Cui, Jian Liu +1

Natural language inference (NLI) is a fundamental NLP task, investigating the entailment relationship between two texts. Popular NLI datasets present the task at sentence-level. Wh…

cs.AI20201 cited

Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning

Yuncheng Hua, Yuan-Fang Li, Gholamreza Haffari +2

A compelling approach to complex question answering is to convert the question to a sequence of actions, which can then be executed on the knowledge base to yield the answer, aka t…