activity
20172026
most citedA Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis

29 citations · 55 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2026

Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model

Zhe Huang, Peng Wang, Yan Zheng +2

Product bundling boosts e-commerce revenue by recommending complementary item combinations. However, existing methods face two critical challenges: (1) collaborative filtering appr…

cs.CL2024★ 5 cited

Enhancing Large Language Model with Decomposed Reasoning for Emotion Cause Pair Extraction

Jialiang Wu, Yi Shen, Ziheng Zhang +1

Emotion-Cause Pair Extraction (ECPE) involves extracting clause pairs representing emotions and their causes in a document. Existing methods tend to overfit spurious correlations,…

cs.CL2022

Constrained Sequence-to-Tree Generation for Hierarchical Text Classification

Chao Yu, Yi Shen, Yue Mao +1

Hierarchical Text Classification (HTC) is a challenging task where a document can be assigned to multiple hierarchically structured categories within a taxonomy. The majority of pr…

cs.CL2021

Hybrid Curriculum Learning for Emotion Recognition in Conversation

Lin Yang, Yi Shen, Yue Mao +1

Emotion recognition in conversation (ERC) aims to detect the emotion label for each utterance. Motivated by recent studies which have proven that feeding training examples in a mea…

cs.CV2021★ 5 cited

Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment

Yin Zhao, Minquan Wang, Longjun Cai

Eliminating the covariate shift cross domains is one of the common methods to deal with the issue of domain shift in visual unsupervised domain adaptation. However, current alignme…

cs.CV2021★ 8 cited

Pairwise Emotional Relationship Recognition in Drama Videos: Dataset and Benchmark

Xun Gao, Yin Zhao, Jie Zhang +1

Recognizing the emotional state of people is a basic but challenging task in video understanding. In this paper, we propose a new task in this field, named Pairwise Emotional Relat…