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20192023
most citedAn End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification

18 citations · 18 across the 5 of their papers we have counts for

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cs.CL2023

PAI at SemEval-2023 Task 2: A Universal System for Named Entity Recognition with External Entity Information

Long Ma, Kai Lu, Tianbo Che +3

The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained named entities in low-context situations and noisy scenarios like the presence of spelling mistakes and t…

cs.CL2021

A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification

Guang Liu, Hailong Huang, Yuzhao Mao +3

Data augmentation (DA) aims to generate constrained and diversified data to improve classifiers in Low-Resource Classification (LRC). Previous studies mostly use a fine-tuned Langu…

cs.CL2021

Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup

Guang Liu, Yuzhao Mao, Hailong Huang +2

Mixup is a recent regularizer for current deep classification networks. Through training a neural network on convex combinations of pairs of examples and their labels, it imposes l…

cs.CL2020

DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation

Yuzhao Mao, Qi Sun, Guang Liu +4

Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems. Existing studies on ERC primarily focus on summarizing the context informatio…

cs.CL201918 cited

An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification

Yue Ma, Zengfeng Zeng, Dawei Zhu +5

This paper describes our approach in DSTC 8 Track 4: Schema-Guided Dialogue State Tracking. The goal of this task is to predict the intents and slots in each user turn to complete…