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Found 15 papers, 4 papers with code
On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training
In this study, we propose to enhance the ABSA robustness by systematically rethinking the bottlenecks from all possible angles, including model, data, and training.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
Conversational Semantic Role Labeling with Predicate-Oriented Latent Graph
In this work, we investigate the integration of a latent graph for CSRL.
Nonautoregressive Encoder-Decoder Neural Framework for End-to-End Aspect-Based Sentiment Triplet Extraction
Aspect-based sentiment triplet extraction (ASTE) aims at recognizing the joint triplets from texts, i. e., aspect terms, opinion expressions, and correlated sentiment polarities.
Ranked #3 on
Aspect Sentiment Triplet Extraction
on ASTE-Data-V2
Rethinking Boundaries: End-To-End Recognition of Discontinuous Mentions with Pointer Networks
A majority of research interests in irregular (eg, nested or discontinuous) named entity recognition (NER) have been paid on nested entities, while discontinuous entities received limited attention.
Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extractionwith Rich Syntactic Knowledge
In this paper, we propose to enhance the pair-wise aspect and opinion terms extraction (PAOTE) task by incorporating rich syntactic knowledge.
Improving Text Understanding via Deep Syntax-Semantics Communication
Recent studies show that integrating syntactic tree models with sequential semantic models can bring improved task performance, while these methods mostly employ shallow integration of syntax and semantics.
Nominal Compound Chain Extraction: A New Task for Semantic-enriched Lexical Chain
Lexical chain consists of cohesion words in a document, which implies the underlying structure of a text, and thus facilitates downstream NLP tasks.
Retrofitting Structure-aware Transformer Language Model for End Tasks
We consider retrofitting structure-aware Transformer-based language model for facilitating end tasks by proposing to exploit syntactic distance to encode both the phrasal constituency and dependency connection into the language model.
Mimic and Conquer: Heterogeneous Tree Structure Distillation for Syntactic NLP
Syntax has been shown useful for various NLP tasks, while existing work mostly encodes singleton syntactic tree using one hierarchical neural network.
High-order Refining for End-to-end Chinese Semantic Role Labeling
Current end-to-end semantic role labeling is mostly accomplished via graph-based neural models.
Deceptive Opinion Spam Detection Using Neural Network
Deceptive opinion spam detection has attracted significant attention from both business and research communities.
