Search Results for author:
Found 19 papers, 5 papers with code
Multi-task Peer-Review Score Prediction
To handle the small size of published datasets on the target aspect of scores, we propose a multi-task approach to leverage additional information from other aspects of scores for improving the performance of the target.
HSCNN: A Hybrid-Siamese Convolutional Neural Network for Extremely Imbalanced Multi-label Text Classification
The data imbalance problem is a crucial issue for the multi-label text classification.
Ranked #11 on
Spectral Reconstruction
on ARAD-1K
CaDRec: Contextualized and Debiased Recommender Model
To tackle the skewed distribution, we propose two strategies for disentangling interactions: (1) modeling individual biases to learn unbiased item embeddings, and (2) incorporating item popularity with positional encoding.
NFARec: A Negative Feedback-Aware Recommender Model
In this paper, we propose a negative feedback-aware recommender model (NFARec) that maximizes the leverage of negative feedback.
Enhanced Coherence-Aware Network with Hierarchical Disentanglement for Aspect-Category Sentiment Analysis
To address the issue of multiple aspect categories and sentiment entanglement, we propose a hierarchical disentanglement module to extract distinct categories and sentiment features.
Abstract, Rationale, Stance: A Joint Model for Scientific Claim Verification
In addition, we enhance the information exchanges and constraints among tasks by proposing a regularization term between the sentence attention scores of abstract retrieval and the estimated outputs of rational selection.
A Neural Local Coherence Analysis Model for Clarity Text Scoring
Local coherence relation between two phrases/sentences such as cause-effect and contrast gives a strong influence of whether a text is well-structured or not.
Multi-task Learning for Automated Essay Scoring with Sentiment Analysis
Multi-task learning models, one of the deep learning techniques that have recently been applied to many NLP tasks, demonstrate the vast potential for AES.
DeepMet: A Reading Comprehension Paradigm for Token-level Metaphor Detection
Machine metaphor understanding is one of the major topics in NLP.
Semi-Automatic Construction and Refinement of an Annotated Corpus for a Deep Learning Framework for Emotion Classification
Therefore, this paper proposes a method of creating a semi-automatically constructed emotion corpus.
A Dataset of Crowdsourced Word Sequences: Collections and Answer Aggregation for Ground Truth Creation
To ensure the quality of the crowdsourced data, people can assign multiple workers to one question and then aggregate the multiple answers with diverse quality into a golden one.
Text Categorization by Learning Predominant Sense of Words as Auxiliary Task
Distributions of the senses of words are often highly skewed and give a strong influence of the domain of a document.
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text Categorization
The lower the HS level, the less the categorization performance.
Annotating the Focus of Negation in Japanese Text
As a foundation for developing a negation focus detector for Japanese, we have annotated textdata of {``}Rakuten Travel: User review data{''} and the newspaper subcorpus of the {``}Balanced Corpus of Contemporary Written Japanese{''} with labels proposed in our annotation scheme.
