Search Results for author:
Found 9 papers, 5 papers with code
UniDrop: A Simple yet Effective Technique to Improve Transformer without Extra Cost
Therefore, in this paper, we integrate different dropout techniques into the training of Transformer models.
Ranked #1 on
Machine Translation
on IWSLT2014 English-German
Transformer-based Multi-Aspect Modeling for Multi-Aspect Multi-Sentiment Analysis
To facilitate the research of ABSA, NLPCC 2020 Shared Task 2 releases a new large-scale Multi-Aspect Multi-Sentiment (MAMS) dataset.
Opinion Transmission Network for Jointly Improving Aspect-oriented Opinion Words Extraction and Sentiment Classification
In this paper, we propose a novel joint model, Opinion Transmission Network (OTN), to exploit the potential bridge between ALSC and AOWE to achieve the goal of facilitating them simultaneously.
Attention Transfer Network for Aspect-level Sentiment Classification
In neural network-based methods for ASC, most works employ the attention mechanism to capture the corresponding sentiment words of the opinion target, then aggregate them as evidence to infer the sentiment of the target.
Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction
To validate the feasibility and compatibility of GTS, we implement three different GTS models respectively based on CNN, BiLSTM, and BERT, and conduct experiments on the aspect-oriented opinion pair extraction and opinion triplet extraction datasets.
Ranked #3 on
Aspect Sentiment Triplet Extraction
on SemEval
Dynamic Programming Principle for Backward Doubly Stochastic Recursive Optimal Control Problem and Sobolev Weak Solution of The Stochastic Hamilton-Bellman Equation
In this paper, we study backward doubly stochastic recursive optimal control problem where the cost function is described by the solution of a backward doubly stochastic differential equation.
Probability Optimization and Control
Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction
In this paper, we propose a novel model to transfer these opinions knowledge from resource-rich review sentiment classification datasets to low-resource task TOWE.
Aspect-oriented Opinion Extraction
General Classification
+1
Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling
In this paper, we propose a novel sequence labeling subtask for ABSA named TOWE (Target-oriented Opinion Words Extraction), which aims at extracting the corresponding opinion words for a given opinion target.
Aspect-oriented Opinion Extraction
target-oriented opinion words extraction
Improving Review Representations with User Attention and Product Attention for Sentiment Classification
Recently, some works achieved improvement by incorporating user and product information to generate a review representation.
