activity
20132025
most citedIntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

158 citations · 716 across the 49 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2023★ 1 cited

Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions

Jie Zhao, Ziyu Guan, Wei Zhao +2

Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task. However, unprofessional users also show an inc…

cs.CL2019★ 17 cited

MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models

Boyuan Pan, Yazheng Yang, Hao Li +4

Machine Comprehension (MC) is one of the core problems in natural language processing, requiring both understanding of the natural language and knowledge about the world. Rapid pro…

cs.CL2019★ 1 cited

Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference

Boyuan Pan, Yazheng Yang, Zhou Zhao +3

Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), is one of the most important problems in natural language processing. It requires to infer the…

cs.CL2017★ 10 cited

Dialogue Act Recognition via CRF-Attentive Structured Network

Zheqian Chen, Rongqin Yang, Zhou Zhao +2

Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention. Cur…

cs.CL2017★ 2 cited

Keyword-based Query Comprehending via Multiple Optimized-Demand Augmentation

Boyuan Pan, Hao Li, Zhou Zhao +2

In this paper, we consider the problem of machine reading task when the questions are in the form of keywords, rather than natural language. In recent years, researchers have achie…

cs.CL2017★ 15 cited

Smarnet: Teaching Machines to Read and Comprehend Like Human

Zheqian Chen, Rongqin Yang, Bin Cao +3

Machine Comprehension (MC) is a challenging task in Natural Language Processing field, which aims to guide the machine to comprehend a passage and answer the given question. Many e…