#PROJECT2020 #NLP365

NLP Papers Summary

One NLP blog post per day for 365 days. 1 > 0

62

blog posts

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Data Science

Day 365: NLP Papers Summary – A Survey on Knowledge Graph Embedding

Knowledge Graph Embeddings Knowledge graph stores real-world facts in the form of RDF-style triplets. Knowledge graph embedding has been used to convert these facts into…
Data Science

Day 281: NLP Papers Summary – Knowledge Reasoning over Knowledge Graph I

Reasoning over knowledge graphs allows you to discover new knowledge and conclusions from existing data. There are three categories of reasoning methods: Rule-based Distribution representation-based…
Data Science

Day 236: NLP Papers Summary – A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts

Objectives and Contributions Used BERT to perform sentiment analysis and key entity detection on financial texts. We consider key entity detection as a sentence matching…
Data Science

Day 234: NLP Papers Summary – Topic Modeling in Financial Documents

Objectives and Contributions Applied topic modelling to quarterly earnings call transcripts of companies. The earnings call transcripts are relative unstructured and consists of Q&A session.…
Data Science
Day 232: NLP Papers Summary – Building and Exploring an EKG for Investment Analysis – Deployment and Related Work
Data Science
Day 231: NLP Papers Summary – Building and Exploring an EKG for Investment Analysis – Building Knowledge Graphs
Data Science
Day 230: NLP Papers Summary – Building and Exploring an EKG for Investment Analysis – Approach Overview
Data Science
Day 229: NLP Papers Summary – Building and Exploring an EKG for Investment Analysis – Introduction and Challenges
Data Science
Day 226: NLP Papers Summary – Anticipating Stock Market of the Renowned Companies: A Knowledge Graph Approach I
Data Science
Day 225: NLP Papers Summary – Architecture of Knowledge Graph Construction Techniques
Data Science
Day 206: NLP Papers Summary – Transformers and Pointer-Generator Networks for Abstractive Summarization
Data Science
Day 192: NLP Papers Summary – Guiding Extractive Summarization with Question-Answering Rewards
Data Science
Day 188: NLP Papers Summary – A Supervised Approach to Extractive Summarisation of Scientific Papers
Data Science
Day 186: NLP Papers Summary – Contextualizing Citations for Scientific Summarization using Word Embeddings and Domain Knowledge
Data Science
Day 185: NLP Papers Summary – A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
Data Science
Day 178: NLP Papers Summary – GPT-3 : Broader Impacts
Data Science
Day 177: NLP Papers Summary – GPT-3 : Limitations
Data Science
Day 176: NLP Papers Summary – GPT-3 : Training and Evaluation Methods
Data Science
Day 175: NLP Papers Summary – GPT-3 : Introduction and Context
Data Science
Day 174: NLP Papers Summary – PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Data Science
Day 167: NLP Papers Summary – Ontology-Aware Clinical Abstractive Summarization
Data Science
Day 166: NLP Papers Summary – Publicly Available Clinical BERT Embeddings
Data Science
Day 161: NLP Papers Summary – BLEURT: Learning Robust Metrics for Text Generation
Data Science
Day 160: NLP Papers Summary – Extractive Summarization as Text Matching
Data Science
Day 159: NLP Papers Summary – ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network
Data Science
Day 158: NLP Papers Summary – Embarrassingly Simple Unsupervised Aspect Extraction
Data Science
Day 157: NLP Papers Summary – Explainable Prediction of Medical Codes from Clinical Text
Data Science
Day 156: NLP Papers Summary – Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
Data Science
Day 155: NLP Papers Summary – TRAIN ONCE, TEST ANYWHERE: ZERO-SHOT LEARNING FOR TEXT CLASSIFICATION
Data Science
Day 154: NLP Papers Summary – Contextual Embeddings: When Are They Worth It?
Data Science
Day 153: NLP Papers Summary – Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations
Data Science
Day 152: NLP Papers Summary – OPINIONDIGEST: A Simple Framework for Opinion Summarization
Data Science
Day 151: NLP Papers Summary – A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
Data Science
Day 150: NLP Papers Summary – Will-They-Won’t-They: A Very Large Dataset for Stance Detection on Twitter
Data Science
Day 149: NLP Papers Summary – MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs
Data Science
Day 148: NLP Papers Summary – A Transformer-based Approach for Source Code Summarization
Data Science
Day 147: NLP Papers Summary – Two Birds, One Stone: A Simple, Unified Model for Text Generation from Structured and Unstructured Data
Data Science
Day 146: NLP Papers Summary – Exploring Content Selection in Summarization of Novel Chapters
Data Science
Day 145: NLP Papers Summary – SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization
Data Science
Day 144: NLP Papers Summary – Attend to Medical Ontologies: Content Selection for Clinical Abstractive Summarization
Data Science
Day 143: NLP Papers Summary – Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records
Data Science
Day 142: NLP Papers Summary – Measuring Emotions in the COVID-19 Real World Worry Dataset
Data Science
Day 141: NLP Papers Summary – TextAttack: A Framework for Adversarial Attacks in Natural Language Processing
Data Science
Day 140: NLP Papers Summary – Multimodal Machine Learning for Automated ICD Coding
Data Science
Day 139: NLP Papers Summary – Neural Approaches to Conversational AI – Conclusion & Research Trends
Data Science
Day 138: NLP Papers Summary – Neural Approaches to Conversational AI – Conversational AI in Industry
Data Science
Day 137: NLP Papers Summary – Neural Approaches to Conversational AI – Social Bot’s Landscape
Data Science
Day 136: NLP Papers Summary – Neural Approaches to Conversational AI – Social Bot’s Challenges
Data Science
Day 135: NLP Papers Summary – Neural Approaches to Conversational AI – E2E Social Bots
Data Science
Day 134: NLP Papers Summary – Neural Approaches to Conversational AI – NLG and E2E
Data Science
Day 133: NLP Papers Summary – Neural Approaches to Conversational AI – NLU and DST
Data Science
Day 132: NLP Papers Summary – Neural Approaches to Conversational AI – Task-Oriented Systems (Evaluation Metrics)
Data Science
Day 131: NLP Papers Summary – Neural Approaches to Conversational AI – Task-Oriented Systems (Introduction)
Data Science
Day 130: NLP Papers Summary – Neural Approaches to Conversational AI – Text-QA (MRC)
Data Science
Day 129: NLP Papers Summary – Neural Approaches to Conversational AI – KB-QA (Neural Methods)
Data Science
Day 128: NLP Papers Summary – Neural Approaches to Conversational AI – KB-QA (Symbolic Methods)
Data Science
Day 127: NLP Papers Summary – Neural Approaches to Conversational AI – Introduction
Data Science
Day 126: NLP Papers Summary – Neural News Recommendation with Topic-Aware News Representation
Data Science
Day 125: NLP Papers Summary – A2N: Attending to Neighbors for Knowledge Graph Inference
Data Science
Day 124: NLP Papers Summary – TLDR: Extreme Summarization of Scientific Documents
Data Science
Day 123: NLP Papers Summary – Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
Data Science
Day 122: NLP Papers Summary – Applying BERT to Document Retrieval with Birch
Data Science
Day 121: NLP Papers Summary – Concept Pointer Network for Abstractive Summarization
Data Science
Day 120: NLP Papers Summary – A Simple Theoretical Model of Importance for Summarization
Data Science
Day 119: NLP Papers Summary – An Argument-Annotated Corpus of Scientific Publications
Data Science
Day 118: NLP Papers Summary – Extractive Summarization of Long Documents by Combining Global and Local Context
Data Science
Day 117: NLP Papers Summary – Abstract Text Summarization: A Low Resource Challenge
Data Science
Day 116: NLP Papers Summary – Data-driven Summarization of Scientific Articles
Data Science
Day 115: NLP Papers Summary – SCIBERT: A Pretrained Language Model for Scientific Text
Data Science
Day 114: NLP Papers Summary – A Summarization System for Scientific Documents
Data Science
Day 113: NLP Papers Summary – On Extractive and Abstractive Neural Document Summarization with Transformer Language Models
Data Science
Day 112: NLP Papers Summary – A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis
Data Science
Day 111: NLP Papers Summary – The Risk of Racial Bias in Hate Speech Detection
Data Science
Day 110: NLP Papers Summary – Double Embeddings and CNN-based Sequence Labelling for Aspect Extraction
Data Science
Day 109: NLP Papers Summary – Studying Summarization Evaluation Metrics in the Appropriate Scoring Range
Data Science
Day 108: NLP Papers Summary – Simple BERT Models for Relation Extraction and Semantic Role Labelling
Data Science
Day 107: NLP Papers Summary – Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization
Data Science
Day 106: NLP Papers Summary – An Unsupervised Neural Attention Model for Aspect Extraction
Data Science
Day 105: NLP Papers Summary – Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks
Data Science
Day 104: NLP Papers Summary – SentiHood: Targeted Aspect Based Sentiment Analysis Dataset for Urban Neighbourhoods
Data Science
Day 103: NLP Papers Summary – Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
Data Science
Day 102: NLP Papers Summary – Implicit and Explicit Aspect Extraction in Financial Microblogs