Conference

Jointprop:Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation
Semi-supervised learning has been an important approach to address challenges in extracting entities and relations from limited data. …
Multi-Scale Receptive Field Graph Model for Emotion Recognition in Conversations
Emotion recognition in conversations (ERC) has gained more attention, where contextual information modeling and multimodal fusion have …
Zero-Shot Text Classification via Self-Supervised Tuning
Existing solutions to zero-shot text classification either conduct prompting with pre-trained language models, which is sensitive to …
InfoCTM:A Mutual Information Maximization Perspective of Cross-lingual Topic Modeling
Cross-lingual topic models have been prevalent for cross-lingual text analysis by revealing aligned latent topics. However, most …
Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Prediction
Modern Review Helpfulness Prediction systems are dependent upon multiple modalities, typically texts and images. Unfortunately, those …
Attentive Gated Lexicon Reader with Contrastive Contextual Co-Attention for Sentiment Classification
This paper proposes a new neural architecture that exploits readily available sentiment lexicon resources. The key idea is that that …
Audio-Visual Domain Adaptation Feature Fusion for Speech Emotion Recognition
Speech emotion recognition has made significant progress in recent years, in which feature representation learning has been paid more …
Is Discourse Role Important for Emotion Recognition in Conversation?
A conversation is a sequence of utterances, where each utterance plays a specific discourse role while expressing a particular emotion. …
Long Range Graph Benchmark
Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm generally exchange information between 1-hop neighbors …
Certified Robustness Against Natural Language Attacks by Causal Intervention
Deep learning models have achieved great success in many fields, yet they are vulnerable to adversarial examples. This paper follows a …