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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 Natural Language Processing Jacob Eisenstein 711 survey 154.02
2 Natural Language Processing Jacob Eisenstein 711 survey 145.75
3 Natural Language Processing Jacob Eisenstein 711 survey 141.26
4 Tackling the Limits of Deep Learning for NLP Richard Socher resource 140.67
5 A Technical Introduction to Statistical Natural Language Processing Jacob Eisenstein 133 survey 140.03
6 Neural Network Methods for Natural Language Processing Yoav Goldberg 713 survey 140.02
7 A Latent Variable Recurrent Neural Network for Discourse-Driven Language Models Yangfeng Ji, Gholamreza Haffari, Jacob Eisenstein 999 paper 138.34
8 Multilingual Language Processing From Bytes Dan Gillick, Cliff Brunk, Oriol Vinyals, Amarnag Subramanya 999 paper 137.60
9 Neural Semantic Role Labeling with Dependency Path Embeddings Michael Roth, Mirella Lapata 999 paper 136.87
10 Topics, Trends, and Resources in NLP Mohit Bansal 133 tutorial 135.52
11 Speech and Language Processing Daniel Jurafsky, James H. Martin 133 survey 134.27
12 Predicting Structures in NLP Constrained Conditional Models and Integer Linear Programming Dan Goldwasser, Vivek Srikumar, Dan Roth 972 tutorial 133.85
13 Transition-Based Dependency Parsing with Stack Long Short-Term Memory Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, Noah A.... 999 paper 133.20
14 LSTM CCG Parsing Mike Lewis, Kenton Lee, Luke Zettlemoyer 999 paper 132.44
15 Weighting Finite-State Transductions With Neural Context Pushpendre Rastogi, Ryan Cotterell, Jason Eisner 999 paper 131.12
16 Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing Vinodkumar Prabhakaran, William L. Hamilton, Dan McFarland, Dan Jur... 999 paper 130.40
17 Information Extraction Sunita Sarawagi 232 survey 129.96
18 Integer Linear Programming in NLP Constrained Conditional Models Ming-Wei Chang, Nick Rizzolo, Dan Roth 181 tutorial 128.31
19 Dependency Parsing: Past, Present, and Future Wenliang Chen, Zhenghua Li, Min Zhang 254 tutorial 128.29
20 LSTM Shift-Reduce CCG Parsing Wenduan Xu 999 paper 127.43
21 Natural Language Data Management and Interfaces Yunyao Li, Davood Rafiei 974 tutorial 126.24
22 A Primer on Neural Network Models for Natural Language Processing Yoav Goldberg 711 survey 126.00
23 Natural language processing: an introduction Prakash M Nadkarni, Lucila Ohno-Machado, Wendy W Chapman 112 survey 125.88
24 Recurrent Memory Networks for Language Modeling Ke Tran, Arianna Bisazza, Christof Monz 999 paper 125.67
25 Gimli: open source and high-performance biomedical name recognition David Campos, Sergio Matos, Jose Oliveira 999 paper 125.64
26 Design Challenges and Misconceptions in Named Entity Recognition Yoav Goldberg 232 lecture 125.23
27 Automatic Semantic Role Labeling Scott Wen-tau Yih, Kristina Toutanova 367 tutorial 125.19
28 Natural Language Processing with Python Steven Bird, Ewan Klein, Edward Loper 132 survey 124.92
29 Robust Subgraph Generation Improves Abstract Meaning Representation Parsing Keenon Werling, Gabor Angeli, Christopher D. Manning 999 paper 124.59
30 A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization Lu Wang, Hema Raghavan, Vittorio Castelli, Radu Florian, Claire Cardie 999 paper 124.18
31 Codra: A Novel Discriminative Framework for Rhetorical Analysis Shafiq Joty, Giuseppe Carenini, Raymond T. Ng 999 paper 123.80
32 Semantic Role Labeling Past, Present and Future Lluis Marquez 367 tutorial 122.15
33 Neural Architectures for Named Entity Recognition Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya K... 999 paper 121.94
34 Joint Event Extraction via Recurrent Neural Networks Thien Huu Nguyen, Kyunghyun Cho, Ralph Grishman 999 paper 121.79
35 Methods and Theories for Large-scale Structured Prediction Xu Sun and Yansong Feng 972 tutorial 121.41
36 Globally Normalized Transition-Based Neural Networks Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessan... 999 paper 120.76
37 Tailoring Continuous Word Representations for Dependency Parsing Mohit Bansal, Kevin Gimpel, Karen Livescu 999 paper 120.27
38 Scholarly Data Mining: Making Sense of Scientific Literature Horacio Saggion, Francesco Ronzano 974 tutorial 120.27
39 Scholarly Data Mining: Making Sense of Scientific Literature Horacio Saggion & Francesco Ronzano 974 tutorial 120.27
40 Semantic Role Labeling: An Introduction to the Special Issue Lluis Marquez, Xavier Carreras, Kenneth C.Litkowski, Suzanne Stevenson 367 survey 119.71
41 Capturing Dependency Syntax with "Deep" Sequential Models Yoav Goldberg 711 tutorial 119.64
42 Opinion mining and sentiment analysis Bo Pang and Lillian Lee 381 survey 118.93
43 Recent Advances in Document Summarization Jin-ge Yao, Xiaojun Wan, Jianguo Xiao 421 survey 118.89
44 Machine Learning for NLP Charu C. Aggarwal 711 survey 118.33
45 Generalized Transition-based Dependency Parsing via Control Parameters Bernd Bohnet, Ryan McDonald, Emily Pitler, Ji Ma 999 paper 118.09
46 End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF Xuezhe Ma, Eduard Hovy 999 paper 117.90
47 Modality and Negation in Natural Language Processing Roser Morante 112 tutorial 117.47
48 Neural Networks For Negation Scope Detection Federico Fancellu, Adam Lopez, Bonnie Webber 999 paper 117.35
49 Transfer Learning - Machine Learnings Next Frontier Sebastian Ruder 978 tutorial 117.30
50 Learning and Inference in Structured Prediction Models Kai-Wei Chang, Gourab Kundu, Dan Roth, Vivek Srikumar tutorial 117.27