Search Results for author:
Found 74 papers, 10 papers with code
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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Financial Opinion Mining
In this tutorial, we will show where we are and where we will be to those researchers interested in this topic.
Learning to Generate Explanation from e-Hospital Services for Medical Suggestion
Explaining the reasoning of neural models has attracted attention in recent years.
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.
Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text Generation
In this paper, we address the hallucination problem commonly found in natural language generation tasks.
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.
Large Language Models Perform Diagnostic Reasoning
We explore the extension of chain-of-thought (CoT) prompting to medical reasoning for the task of automatic diagnosis.
Self-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations
Finally, we perform ICL for the test input with the pseudo-input-label pairs as demonstrations.
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.
FinTech for Social Good: A Research Agenda from NLP Perspective
Making our research results positively impact on society and environment is one of the goals our community has been pursuing recently.
Dynamic Graph Transformer for Implicit Tag Recognition
Textual information extraction is a typical research topic in the NLP community.
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).
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.
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.
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.
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.
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.
Chinese Preposition Selection for Grammatical Error Diagnosis
Misuse of Chinese prepositions is one of common word usage errors in grammatical error diagnosis.
Detection, Disambiguation and Argument Identification of Discourse Connectives in Chinese Discourse Parsing
In this paper, we investigate four important issues together for explicit discourse relation labelling in Chinese texts: (1) discourse connective extraction, (2) linking ambiguity resolution, (3) relation type disambiguation, and (4) argument boundary identification.
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 Tense Labelling and Causal Analysis
This paper explores the role of tense information in Chinese causal analysis.
Novel Word Embedding and Translation-based Language Modeling for Extractive Speech Summarization
Word embedding methods revolve around learning continuous distributed vector representations of words with neural networks, which can capture semantic and/or syntactic cues, and in turn be used to induce similarity measures among words, sentences and documents in context.
Detecting Word Usage Errors in Chinese Sentences for Learning Chinese as a Foreign Language
By utilizing certain combination of the sets of features, we can construct a system that favors precision or recall.
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.
Subtask Mining from Search Query Logs for How-Knowledge Acceleration
How-knowledge is indispensable in daily life, but has relatively less quantity and poorer quality than what-knowledge in publicly available knowledge bases.
Leveraging Word Embeddings for Spoken Document Summarization
Owing to the rapidly growing multimedia content available on the Internet, extractive spoken document summarization, with the purpose of automatically selecting a set of representative sentences from a spoken document to concisely express the most important theme of the document, has been an active area of research and experimentation.
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.
Development of a Web-Scale Chinese Word N-gram Corpus with Parts of Speech Information
Web provides a large-scale corpus for researchers to study the language usages in real world.
NTUSocialRec: An Evaluation Dataset Constructed from Microblogs for Recommendation Applications in Social Networks
This paper proposes a method to construct an evaluation dataset from microblogs for the development of recommendation systems.
Mining Sentiment Words from Microblogs for Predicting Writer-Reader Emotion Transition
The conversations between posters and repliers in microblogs form a valuable writer-reader emotion corpus.
