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Neural End-to-End Learning for Computational Argumentation Mining


We investigate neural techniques for end-to-end computational argumentation min-ing (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including a multi-task learning setup. Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results. In contrast, less complex (local) tagging models based on BiL-STMs perform robustly across classification scenarios, being able to catch long-range dependencies inherent to the AM problem. Moreover, we find that jointly learning ‘natural’ subtasks, in a multi-task learning setup, improves performance.



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# Title Author Topic Medium Score
1 Codra: A Novel Discriminative Framework for Rhetorical Analysis Shafiq Joty, Giuseppe Carenini, Raymond T. Ng 999 paper 176.38
2 Similarity-driven Semantic Role Induction via Graph Partitioning Joel Lang, Mirella Lapata 999 paper 166.09
3 Highlights of EMNLP 2017: Exciting Datasets, Return of the Clusters, and More! Sebastian Ruder 641 resource 163.70
4 Discriminative Syntax-based Word Ordering for Text Generation Yue Zhang, Stephen Clark 999 paper 162.53
5 NLP's ImageNet moment has arrived Sebastian Ruder 862 resource 138.32
7 Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience Ismael Rafols, Martin Meyer 999 paper 137.63
8 Recurrent Neural Network Tutorial, Part 4 – Implementing a GRU/LSTM RNN with Python and Theano Denny Britz 742 tutorial 136.77
9 NLP’s generalization problem, and how researchers are tackling it Ana Marasovic 711 resource 136.42
10 Recurrent Neural Networks Tutorial, Part 2 - Implementing a RNN with Python, Numpy, and Theano Denny Britz 741 tutorial 135.81
11 Recent Advances in Document Summarization Jin-ge Yao, Xiaojun Wan, Jianguo Xiao 421 survey 134.78
12 RNNs in Tensorflow, a Practical Guide and Undocumented Features Denny Britz 741 tutorial 132.94
13 Transfer Learning - Machine Learnings Next Frontier Sebastian Ruder 978 tutorial 132.81
14 Recurrent Neural Networks Tutorial, Part 3- Backpropagation Through Time and Vanishing Gradients Denny Britz 741 tutorial 131.79
15 Gimli: open source and high-performance biomedical name recognition David Campos, Sergio Matos, Jose Oliveira 999 paper 131.06
16 Recurrent Neural Networks Tutorial, Part 1 - Introduction to RNNs Denny Britz 741 tutorial 129.71
17 DEEP LEARNING FOR CHATBOTS, PART 1 - INTRODUCTION Denny Britz 445 tutorial 129.28
18 Deep Learning for NLP Best Practices Sebastian Ruder 713 tutorial 127.18
19 Bayesian Statistics explained to Beginners in Simple English NSS 102 tutorial 126.92
20 An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder 829 tutorial 124.73
21 The data that transformed AI research—and possibly the world Dave Gershgorn 107 resource 124.63
22 Neural Information Retrieval: At the End of the Early Years Kezban Dilek Onal, Ye Zhang, Ismail Sengor Altingovde, Md Mustafizur Rahman, Pinar Karagoz, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek K 713 resource 123.18
23 The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution Chun-Ting Zhang 999 paper 123.02
24 Lexicalization and Generative Power in Ccg Marco Kuhlmann, Alexander Koller, Giorgio Satta 999 paper 122.07
25 A Practitioner's Guide to Natural Language Processing (Part I)?—?Processing & Understanding Text Dipanjan (DJ) Sarker 112 resource 121.94
26 Natural Language Processing Made Easy – using SpaCy (in Python) Shivam Bansal 131 tutorial 121.12
27 A survey of cross-lingual embedding models Sebastian Ruder 721 tutorial 120.90
28 Lisbon Machine Learning Summer School Highlights Sebastian Ruder 107 resource 120.63
29 Do Altmetrics Work? Twitter and Ten Other Social Web Services Mike Thelwall, Stefanie Haustein, Vincent Larivière, Cassidy R. Sugimoto 999 paper 119.55
30 A social network's changing statistical properties and the quality of human innovation Brian Uzzi 999 paper 117.61
31 Multi-Task Learning Objectives for Natural Language Processing Author Unknown 133 resource 117.35
32 How do we capture structure in relational data? Matthew Das Sarma 711 resource 116.80
33 An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship J. E. Hirsch 999 paper 114.88
34 An Intuitive Guide to Linear Algebra Kalid Azad 121 tutorial 113.87
35 The Unreasonable Effectiveness of Recurrent Neural Networks Andrej Karpathy 741 survey 113.12
36 spaCy 101: Everything you need to know Author Unknown 731 resource 113.06
37 Rohan & Lenny #3: Recurrent Neural Networks & LSTMs Rohan Kapur 741 tutorial 113.03
38 K-Means & Other Clustering Algorithms: A Quick Intro with Python Nikos Koufos 571 tutorial 112.05
39 spaCy: Named Entities Spacy 232 resource 111.94
40 Negated bio-events: analysis and identification Raheel Nawaz, Paul Thompson, Sophia Ananiadou 999 paper 111.47
41 Many languages, one parser Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, Noah A Smith 999 paper 110.44
42 Natural Language Processing in Artificial Intelligence is almost human-level accurate. Worse yet, it gets smart! Rafal 133 tutorial 110.19
43 The history and meaning of the journal impact factor Eugene Garfield 999 paper 109.17
44 Four deep learning trends from ACL 2017: Part 2 Abigail See 713 resource 109.15
45 Deep Learning from first principles in Python, R and Octave – Part 3 Tinniam V Ganesh 711 resource 108.72
46 Four deep learning trends from ACL 2017: Part 1 Abigail See 713 resource 108.65
47 The 7 NLP Techniques That Will Change How You Communicate in the Future (Part II) James Le 133 resource 107.78
48 State-of-the-art neural coreference resolution for chatbots Thomas Wolf 756 tutorial 106.84
49 A general framework for analysing diversity in science, technology and society Andy Stirling 999 paper 106.47
50 Machine Learning for Humans Vishal Maini, Samer Sabri 134 tutorial 105.02
51 Train Neural Machine Translation Models with Sockeye Felix Hieber, Tobias Domhan 753 tutorial 104.48
52 Written Memories: Understanding, Deriving and Extending the LSTM R2RT 742 resource 103.41
53 An Overview of Proxy-label Approaches for Semi-supervised Learning Sebastian Ruder 581 resource 103.10
54 Word2vec in Python, Part Two: Optimizing Radim Rehurek 721 tutorial 102.94
55 Deep Learning for NLP, advancements and trends in 2017 Javier 711 resource 102.64
56 Automatic Labeling of Semantic Roles Daniel Gildea, Daniel Jurafsky 999 paper 101.83
57 Word embeddings in 2017: Trends and future directions Sebastian Ruder 721 resource 101.23
58 Requests for Research Sebastian Ruder 921 resource 100.96
59 Neural Networks Tutorial – A Pathway to Deep Learning Andy Thomas 711 tutorial 99.54
60 The Definitive Guide to Natural Language Processing Javier Couto 133 tutorial 99.48
61 Language modeling a billion words Nicholas Leonard 742 tutorial 99.32
62 Some Highlights of MILA Deep Learning and Reinforcement Learning Summer Schools 2017 Mostafa Dehghani 857 resource 99.05
63 Gensim integration with scikit-learn and Keras Chinmaya Pancholi 713 library 98.62
64 A Beginner’s Guide to Deep Reinforcement Learning Adam Gibson, Chris Nicholson, Josh Patterson 857 library 98.51
65 Rohan #2: Artificial intelligence, ?Progress/?Time Rohan Kapur 811 tutorial 98.41
66 DeepMind has a bigger plan for its newest Go-playing AI Dave Gershgorn 811 resource 98.18
67 Parsing English in 500 Lines of Python Matthew Honnibal 242 tutorial 97.80
68 Ultimate Guide to Understand & Implement Natural Language Processing (with codes in Python) Shivam Bansal 131 tutorial 97.71
69 Learning AI if You Suck at Math?—?P7?—?The Magic of Natural Language Processing Daniel Jeffries 133 tutorial 97.46
70 Deep Learning for NLP: An Overview of Recent Trends Elvis 711 resource 97.13
71 Language Processing Pipelines Author Unknown 731 resource 97.05
72 Is science becoming more interdisciplinary? Measuring and mapping six research fields over time Alan L. Porter, Ismael Rafols 999 paper 96.95
73 ICML+ACL’18: Structure Back in Play, Translation Wants More Context Andre Martins 956 resource 96.89
74 Vector Calculus: Understanding the Dot Product Kalid Azad 101 tutorial 96.72
75 Python TensorFlow Tutorial – Build a Neural Network Andy Thomas 731 tutorial 96.58
76 An end to end implementation of a Machine Learning pipeline Spandan Madan 107 tutorial 96.45
77 Simple Beginner’s guide to Reinforcement Learning & its implementation Faizan Shaikh 713 tutorial 96.27
78 A comprehensive beginner's guide to create a Time Series Forecast (with Codes in Python) Aarshay Jain 921 resource 96.26
79 Clustering cliques for graph-based summarization of the biomedical research literature Han Zhang, Marcelo Fiszman, Dongwook Shin, Bartomiej Wilkowski, Thomas Rindflesch 999 paper 96.25
80 Analyzing the Meaning of Sentences Steven Bird, Ewan Klein, Edward Loper 721 course 96.03
81 Yet Another Twitter Sentiment Analysis Part 1?—?tackling class imbalance The Rickest Ricky 381 resource 95.94
82 Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences Hongyuan Mei, Mohit Bansal, Matthew R. Walter 999 paper 95.83
83 Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer, Noah A Smith 999 paper 95.76
84 Image-to-Image Translation in Tensorflow Christopher Hesse 731 tutorial 95.68
85 Introduction to Computational Linguistics and Dependency Trees in data science Shivam Bansal 711 resource 95.53
86 BiLSTM-CNN-CRF Implementation for Sequence Tagging UKPLab 231 library 95.48
87 Machine Learning Morteza Shahriari Nia 107 tutorial 95.26
88 Tombones Computer Vision Blog Tomasz Malisiewicz 958 resource 95.22
89 Awesome Python Vinta 131 resource 95.16
90 40 Interview Questions asked at Startups in Machine Learning / Data Science ANALYTICS VIDHYA CONTENT TEAM 107 tutorial 94.94
91 Fundamentals of Deep Learning - Activation Functions and When to Use Them? Dishashree Gupta 711 resource 94.59
92 The NeuroEvolution of Augmenting Topologies (NEAT) Users Page Author Unknown 999 resource 94.16
93 Building a FAQ Chatbot in Python – The Future of Information Searching Yogesh Kulkarni 232 resource 93.89
94 Face recognition with OpenCV, Python, and deep learning Adrian Rosebrock 862 resource 93.85
95 Transfer Learning in Natural Language Processing Prajjwal Bhargava 956 resource 93.84