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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 Highlights of EMNLP 2017: Exciting Datasets, Return of the Clusters, and More! Sebastian Ruder 641 resource 139.42
2 Codra: A Novel Discriminative Framework for Rhetorical Analysis Shafiq Joty, Giuseppe Carenini, Raymond T. Ng 999 paper 132.74
3 Similarity-driven Semantic Role Induction via Graph Partitioning Joel Lang, Mirella Lapata 999 paper 132.45
4 Discriminative Syntax-based Word Ordering for Text Generation Yue Zhang, Stephen Clark 999 paper 121.78
5 Recurrent Neural Networks Tutorial, Part 2 - Implementing a RNN with Python, Numpy, and Theano Denny Britz 741 tutorial 120.15
6 Recurrent Neural Network Tutorial, Part 4 – Implementing a GRU/LSTM RNN with Python and Theano Denny Britz 742 tutorial 117.16
7 Recurrent Neural Networks Tutorial, Part 3- Backpropagation Through Time and Vanishing Gradients Denny Britz 741 tutorial 116.27
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10 RNNs in Tensorflow, a Practical Guide and Undocumented Features Denny Britz 741 tutorial 115.45
11 Recurrent Neural Networks Tutorial, Part 1 - Introduction to RNNs Denny Britz 741 tutorial 114.75
12 DEEP LEARNING FOR CHATBOTS, PART 1 - INTRODUCTION Denny Britz 445 tutorial 114.74
13 The data that transformed AI research—and possibly the world Dave Gershgorn 107 resource 111.29
14 Gimli: open source and high-performance biomedical name recognition David Campos, Sergio Matos, Jose Oliveira 999 paper 110.48
15 NLP's ImageNet moment has arrived Sebastian Ruder 862 resource 110.17
16 Transfer Learning - Machine Learnings Next Frontier Sebastian Ruder 978 tutorial 107.95
17 The h’-Index, Effectively Improving the h-Index Based on the Citation Distribution Chun-Ting Zhang 999 paper 106.92
18 Natural Language Processing Made Easy – using SpaCy (in Python) Shivam Bansal 131 tutorial 106.17
19 Multi-Task Learning Objectives for Natural Language Processing Author Unknown 133 resource 103.53
20 Deep Learning for NLP Best Practices Sebastian Ruder 713 tutorial 103.39
21 NLP’s generalization problem, and how researchers are tackling it Ana Marasovic 711 resource 103.18
22 Bayesian Statistics explained to Beginners in Simple English NSS 102 tutorial 102.98
23 A Practitioner's Guide to Natural Language Processing (Part I)?—?Processing & Understanding Text Dipanjan (DJ) Sarker 112 resource 101.94
24 Recent Advances in Document Summarization Jin-ge Yao, Xiaojun Wan, Jianguo Xiao 421 survey 101.16
25 Lisbon Machine Learning Summer School Highlights Sebastian Ruder 107 resource 99.85
26 K-Means & Other Clustering Algorithms: A Quick Intro with Python Nikos Koufos 571 tutorial 99.40
27 Many languages, one parser Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, Noah A Smith 999 paper 98.54
28 An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder 829 tutorial 97.53
29 An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship J. E. Hirsch 999 paper 96.35
30 Do Altmetrics Work? Twitter and Ten Other Social Web Services Mike Thelwall, Stefanie Haustein, Vincent Larivière, Cassidy R. Sugimoto 999 paper 94.57
31 A survey of cross-lingual embedding models Sebastian Ruder 721 tutorial 93.86
32 spaCy 101: Everything you need to know Author Unknown 731 resource 92.64
33 Four deep learning trends from ACL 2017: Part 1 Abigail See 713 resource 92.47
34 Negated bio-events: analysis and identification Raheel Nawaz, Paul Thompson, Sophia Ananiadou 999 paper 92.41
35 spaCy: Named Entities Spacy 232 resource 91.55
36 An Intuitive Guide to Linear Algebra Kalid Azad 121 tutorial 91.47
37 Natural Language Processing in Artificial Intelligence is almost human-level accurate. Worse yet, it gets smart! Rafal 133 tutorial 91.02
38 Automatic Labeling of Semantic Roles Daniel Gildea, Daniel Jurafsky 999 paper 90.93
39 Is science becoming more interdisciplinary? Measuring and mapping six research fields over time Alan L. Porter, Ismael Rafols 999 paper 90.33
40 DeepMind has a bigger plan for its newest Go-playing AI Dave Gershgorn 811 resource 90.24
41 How do we capture structure in relational data? Matthew Das Sarma 711 resource 89.92
42 Rohan & Lenny #3: Recurrent Neural Networks & LSTMs Rohan Kapur 741 tutorial 89.76
43 The 7 NLP Techniques That Will Change How You Communicate in the Future (Part II) James Le 133 resource 89.49
44 Four deep learning trends from ACL 2017: Part 2 Abigail See 713 resource 88.58
45 State-of-the-art neural coreference resolution for chatbots Thomas Wolf 756 tutorial 88.11
46 Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences Hongyuan Mei, Mohit Bansal, Matthew R. Walter 999 paper 88.08
47 The Unreasonable Effectiveness of Recurrent Neural Networks Andrej Karpathy 741 survey 87.60
48 Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer, Noah A Smith 999 paper 87.27
49 A social network's changing statistical properties and the quality of human innovation Brian Uzzi 999 paper 87.18
50 Lexicalization and Generative Power in Ccg Marco Kuhlmann, Alexander Koller, Giorgio Satta 999 paper 86.33
51 Quadratic entropy and analysis of diversity C. R. Rao 999 paper 86.17
52 A general framework for analysing diversity in science, technology and society Andy Stirling 999 paper 85.92
53 The history and meaning of the journal impact factor Eugene Garfield 999 paper 85.91
54 Word embeddings in 2017: Trends and future directions Sebastian Ruder 721 resource 85.68
55 Python TensorFlow Tutorial – Build a Neural Network Andy Thomas 731 tutorial 84.67
56 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 232 survey 84.45
57 Some Highlights of MILA Deep Learning and Reinforcement Learning Summer Schools 2017 Mostafa Dehghani 857 resource 84.17
58 Webcrow: A Web-Based Crosswords Solver Giovanni Angelini, Marco Ernandes, Marco Gori 999 paper 83.57
59 An Overview of Proxy-label Approaches for Semi-supervised Learning Sebastian Ruder 581 resource 83.51
60 Requests for Research Sebastian Ruder 921 resource 83.43
61 Language Processing Pipelines Author Unknown 731 resource 83.19
62 Deep Learning for NLP, advancements and trends in 2017 Javier 711 resource 83.00
63 The Definitive Guide to Natural Language Processing Javier Couto 133 tutorial 82.65
64 Word2vec in Python, Part Two: Optimizing Radim Rehurek 721 tutorial 82.63
65 Parsing English in 500 Lines of Python Matthew Honnibal 242 tutorial 82.57
66 Deep Learning from first principles in Python, R and Octave – Part 3 Tinniam V Ganesh 711 resource 82.44
67 Neural Networks Tutorial – A Pathway to Deep Learning Andy Thomas 711 tutorial 82.40
68 Train Neural Machine Translation Models with Sockeye Felix Hieber, Tobias Domhan 753 tutorial 82.18
69 Language modeling a billion words Nicholas Leonard 742 tutorial 81.58
70 Deep Learning for NLP: An Overview of Recent Trends Elvis 711 resource 81.50
71 Dialog state tracking, a machine reading approach using a memory-enhanced neural network Julien Perez 999 paper 81.44
72 ICML+ACL’18: Structure Back in Play, Translation Wants More Context Andre Martins 956 resource 81.22
73 Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism Orhan Firat, Kyunghyun Cho, Yoshua Bengio 999 paper 80.66
74 Ultimate Guide to Understand & Implement Natural Language Processing (with codes in Python) Shivam Bansal 131 tutorial 80.49