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Found 46 papers, 8 papers with code
Learning to Generate Explanation from e-Hospital Services for Medical Suggestion
Explaining the reasoning of neural models has attracted attention in recent years.
Financial Opinion Mining
In this tutorial, we will show where we are and where we will be to those researchers interested in this topic.
NTUNLPL at FinCausal 2020, Task 2:Improving Causality Detection Using Viterbi Decoder
In order to provide an explanation of machine learning models, causality detection attracts lots of attention in the artificial intelligence research community.
Semantics-Preserved Data Augmentation for Aspect-Based Sentiment Analysis
Both the issues of data deficiencies and semantic consistency are important for data augmentation.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
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NumHG: A Dataset for Number-Focused Headline Generation
Headline generation, a key task in abstractive summarization, strives to condense a full-length article into a succinct, single line of text.
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models
Inspired by the implicit mental process of how human beings assess explanations, we present a novel approach, Zero-shot Augmentation of Rationale-Answer pairs (ZARA), to automatically construct pseudo-parallel data for self-training by reducing the problem of plausibility judgement to natural language inference.
LED: A Dataset for Life Event Extraction from Dialogs
Our proposed life event dialog dataset and in-depth analysis of IE frameworks will facilitate future research on life event extraction from conversations.
Entity-Aware Dual Co-Attention Network for Fake News Detection
Fake news and misinformation spread rapidly on the Internet.
Dynamic Graph Transformer for Implicit Tag Recognition
Textual information extraction is a typical research topic in the NLP community.
Heterogeneous Recycle Generation for Chinese Grammatical Error Correction
Most recent works in the field of grammatical error correction (GEC) rely on neural machine translation-based models.
NTU\_NLP at SemEval-2020 Task 12: Identifying Offensive Tweets Using Hierarchical Multi-Task Learning Approach
This paper presents our hierarchical multi-task learning (HMTL) and multi-task learning (MTL) approaches for improving the text encoder in Sub-tasks A, B, and C of Multilingual Offensive Language Identification in Social Media (SemEval-2020 Task 12).
A Complete Shift-Reduce Chinese Discourse Parser with Robust Dynamic Oracle
This work proposes a standalone, complete Chinese discourse parser for practical applications.
Fine-grained Financial Opinion Mining: A Survey and Research Agenda
Opinion mining is a prevalent research issue in many domains.
NLP in FinTech Applications: Past, Present and Future
Financial Technology (FinTech) is one of the worldwide rapidly-rising topics in the past five years according to the statistics of FinTech from Google Trends.
Ten Questions in Lifelog Mining and Information Recall
With the advance of science and technology, people are used to record their daily life events via writing blogs, uploading social media posts, taking photos, or filming videos.
MSD-1030: A Well-built Multi-Sense Evaluation Dataset for Sense Representation Models
However, most of these datasets are not designed for evaluating sense embeddings.
Issues and Perspectives from 10,000 Annotated Financial Social Media Data
In this paper, we investigate the annotation of financial social media data from several angles.
MPDD: A Multi-Party Dialogue Dataset for Analysis of Emotions and Interpersonal Relationships
In this paper, we collect the conversions from TV series scripts, and annotate emotion and interpersonal relationship labels on each utterance.
Chinese Discourse Parsing: Model and Evaluation
Chinese discourse parsing, which aims to identify the hierarchical relationships of Chinese elementary discourse units, has not yet a consistent evaluation metric.
Lexicon Guided Attentive Neural Network Model for Argument Mining
Identification of argumentative components is an important stage of argument mining.
Numeracy-600K: Learning Numeracy for Detecting Exaggerated Information in Market Comments
In this paper, we attempt to answer the question of whether neural network models can learn numeracy, which is the ability to predict the magnitude of a numeral at some specific position in a text description.
Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting
Numerals that contain much information in financial documents are crucial for financial decision making.
Correcting Chinese Word Usage Errors for Learning Chinese as a Second Language
For more than 91{\%} of the cases, our system can propose at least one acceptable correction within a list of five candidates.
A Unified RvNN Framework for End-to-End Chinese Discourse Parsing
This paper demonstrates an end-to-end Chinese discourse parser.
A Chinese Writing Correction System for Learning Chinese as a Foreign Language
We present a Chinese writing correction system for learning Chinese as a foreign language.
GenSense: A Generalized Sense Retrofitting Model
In the experiment, we show that the generalized model can outperform previous approaches in three types of experiment: semantic relatedness, contextual word similarity and semantic difference.
Disambiguating False-Alarm Hashtag Usages in Tweets for Irony Detection
The reliability of self-labeled data is an important issue when the data are regarded as ground-truth for training and testing learning-based models.
NTU NLP Lab System at SemEval-2018 Task 10: Verifying Semantic Differences by Integrating Distributional Information and Expert Knowledge
This paper presents the NTU NLP Lab system for the SemEval-2018 Capturing Discriminative Attributes task.
Integrating Subject, Type, and Property Identification for Simple Question Answering over Knowledge Base
Besides, we split a relation in KB into type and property.
NLG301 at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News
Short length, multi-targets, target relation-ship, monetary expressions, and outside reference are characteristics of financial tweets.
NTU-1 at SemEval-2017 Task 12: Detection and classification of temporal events in clinical data with domain adaptation
This study proposes a system to participate in the Clinical TempEval 2017 shared task, a part of the SemEval 2017 Tasks.
Detection of Chinese Word Usage Errors for Non-Native Chinese Learners with Bidirectional LSTM
Selecting appropriate words to compose a sentence is one common problem faced by non-native Chinese learners.
NL2KB: Resolving Vocabulary Gap between Natural Language and Knowledge Base in Knowledge Base Construction and Retrieval
With the demo system called NL2KB in this paper, users can browse which properties in KB side may be mapped to for a given relational pattern in NL side.
Chinese Preposition Selection for Grammatical Error Diagnosis
Misuse of Chinese prepositions is one of common word usage errors in grammatical error diagnosis.
Chinese Tense Labelling and Causal Analysis
This paper explores the role of tense information in Chinese causal analysis.
Fine-Grained Chinese Discourse Relation Labelling
Marker-Sum feature considers total contribution of markers and Marker-Preference feature captures the probability distribution of discourse functions of a representative marker by using preference rule.
Sentence Rephrasing for Parsing Sentences with OOV Words
To deal with this problem, we propose a sentence rephrasing approach to replace each OOV word in a sentence with a popular word of the same named entity type in the training set, so that the knowledge of the word forms can be used for parsing.
