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20192023
most citedLabel-Wise Document Pre-Training for Multi-Label Text Classification

2 citations · 9 across the 14 of their papers we have counts for

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9 papers · 1 filter

cs.CL2023

AKEM: Aligning Knowledge Base to Queries with Ensemble Model for Entity Recognition and Linking

Di Lu, Zhongping Liang, Caixia Yuan +1

This paper presents a novel approach to address the Entity Recognition and Linking Challenge at NLPCC 2015. The task involves extracting named entity mentions from short search que…

cs.CL2023

FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion Recognition

Yuzhao Mao, Di Lu, Xiaojie Wang +1

This paper concentrates on the understanding of interlocutors' emotions evoked in conversational utterances. Previous studies in this literature mainly focus on more accurate emoti…

cs.CL2023

An Asynchronous Updating Reinforcement Learning Framework for Task-oriented Dialog System

Sai Zhang, Yuwei Hu, Xiaojie Wang +1

Reinforcement learning has been applied to train the dialog systems in many works. Previous approaches divide the dialog system into multiple modules including DST (dialog state tr…

cs.CL20221 cited

Co-VQA : Answering by Interactive Sub Question Sequence

Ruonan Wang, Yuxi Qian, Fangxiang Feng +2

Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions…

cs.CL2021

Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue

Han Liu, Caixia Yuan, Xiaojie Wang +3

We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue. To benchmark pr…

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…