7 citations · 30 across the 14 of their papers we have counts for
14 papers
SelectTSL: Prompt-Guided Selective Target Sound Localization in Complex Scenarios
Ziyang Jiang, Yu Chen, Zexu Pan +5
Humans can selectively attend to a target sound and estimate its direction in complex scenarios, whereas such selective localization remains challenging for current deep learning-b…
HCL: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding
Bowen Xing, Ivor W. Tsang
State-of-the-art model for zero-shot cross-lingual spoken language understanding performs cross-lingual unsupervised contrastive learning to achieve the label-agnostic semantic ali…
Exploiting Contextual Target Attributes for Target Sentiment Classification
Bowen Xing, Ivor W. Tsang
Existing PTLM-based models for TSC can be categorized into two groups: 1) fine-tuning-based models that adopt PTLM as the context encoder; 2) prompting-based models that transfer t…
Co-guiding for Multi-intent Spoken Language Understanding
Bowen Xing, Ivor W. Tsang
Recent graph-based models for multi-intent SLU have obtained promising results through modeling the guidance from the prediction of intents to the decoding of slot filling. However…
Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding
Bowen Xing, Ivor W. Tsang
Dual-task dialog language understanding aims to tackle two correlative dialog language understanding tasks simultaneously via leveraging their inherent correlations. In this paper,…
Co-evolving Graph Reasoning Network for Emotion-Cause Pair Extraction
Bowen Xing, Ivor W. Tsang
Emotion-Cause Pair Extraction (ECPE) aims to extract all emotion clauses and their corresponding cause clauses from a document. Existing approaches tackle this task through multi-t…
Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs
Bowen Xing, Ivor W. Tsang
Recent graph-based models for joint multiple intent detection and slot filling have obtained promising results through modeling the guidance from the prediction of intents to the d…
Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling
Bowen Xing, Ivor W. Tsang
Recent joint multiple intent detection and slot filling models employ label embeddings to achieve the semantics-label interactions. However, they treat all labels and label embeddi…
Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning
Bowen Xing, Ivor W. Tsang
Recent years have witnessed the emerging success of leveraging syntax graphs for the target sentiment classification task. However, we discover that existing syntax-based models su…
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition
Bowen Xing, Ivor W. Tsang
The task of joint dialog sentiment classification (DSC) and act recognition (DAR) aims to simultaneously predict the sentiment label and act label for each utterance in a dialog. I…
DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification
Bowen Xing, Ivor Tsang
In aspect-level sentiment classification (ASC), state-of-the-art models encode either syntax graph or relation graph to capture the local syntactic information or global relational…
Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network
Bowen Xing, Ivor W. Tsang
Aspect-level sentiment classification (ASC) aims to predict the fine-grained sentiment polarity towards a given aspect mentioned in a review. Despite recent advances in ASC, enabli…
Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis
Bowen Xing, Ivor W. Tsang
Aspect-based sentiment analysis (ABSA) aims to predict the sentiment expressed in a review with respect to a given aspect. The core of ABSA is to model the interaction between the…
Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis
Bowen Xing, Lejian Liao, Dandan Song +4
Aspect-based sentiment analysis (ABSA) aims to predict fine-grained sentiments of comments with respect to given aspect terms or categories. In previous ABSA methods, the importanc…