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Title:

Neural End-to-End Learning for Computational Argumentation Mining

Abstract:

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
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10 Multiword Expression Processing: A Survey Mathieu Constant, Gül?en Eryi?it, Johanna Monti, Lonneke van der Plas 1122
11 Multilingual Language Processing From Bytes Dan Gillick, Cliff Brunk, Oriol Vinyals, Amarnag Subramanya 9999
12 Joint Event Extraction via Recurrent Neural Networks Thien Huu Nguyen, Kyunghyun Cho, Ralph Grishman 9999
13 Tackling the Limits of Deep Learning for NLP Richard Socher 711
14 Modern Deep Learning Techniques Applied to Natural Language Processing Elvis Saravia, Soujanya Poria 1183
15 A Survey on Deep Learning for Named Entity Recognition Li, Jing and Sun, Aixin and Han, Jianglei and Li, Chenliang 1089
16 Neural Network-Based Abstract Generation for Opinions and Arguments Lu Wang, Wang Ling 1198
17 Encode, Review, and Decode: Reviewer Module for Caption Generation Zhilin Yang, Ye Yuan, Yuexin Wu, Ruslan Salakhutdinov, William W Cohen 9999
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19 Multi-Task Learning Objectives for Natural Language Processing Author Unknown 1065
20 Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task Nan Ding, Sebastian Goodman, Fei Sha, Radu Soricut 9999
21 Codra: A Novel Discriminative Framework for Rhetorical Analysis Shafiq Joty, Giuseppe Carenini, Raymond T. Ng 9999
22 Language+Robotics Mohit Bansal 1340
23 Intro to the Course, Language Modeling Mohit Bansal 1015
24 57 Summaries of Machine Learning and NLP Research Marek Rei 1201
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29 Integer Linear Programming in NLP Constrained Conditional Models Ming-Wei Chang, Nick Rizzolo, Dan Roth 1221
30 Methods and Theories for Large-scale Structured Prediction Xu Sun and Yansong Feng 1262
31 Transition-Based Dependency Parsing with Stack Long Short-Term Memory Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, Noah A.... 9999
32 Topics, Trends, and Resources in NLP Mohit Bansal 1065
33 Generalized Transition-based Dependency Parsing via Control Parameters Bernd Bohnet, Ryan McDonald, Emily Pitler, Ji Ma 9999
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35 Recurrent Memory Networks for Language Modeling Ke Tran, Arianna Bisazza, Christof Monz 9999
36 Automatic Semantic Role Labeling Scott Wen-tau Yih, Kristina Toutanova 1220
37 Transfer Learning - Machine Learnings Next Frontier Sebastian Ruder 1323
38 Transfer Learning - Machine Learning's Next Frontier Sebastian Ruder 9999
39 Do Multi-Sense Embeddings Improve Natural Language Understanding? Jiwei Li, Dan Jurafsky 9999
40 What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment Hongyuan Mei, Mohit Bansal, Matthew R. Walter 9999
41 Recent Advances in Document Summarization Jin-ge Yao, Xiaojun Wan, Jianguo Xiao 1129
42 Harnessing Deep Neural Networks with Logic Rules Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, Eric Xing 9999
43 Adaptive Joint Learning of Compositional and Non-Compositional Phrase Embeddings Kazuma Hashimoto, Yoshimasa Tsuruoka 9999
44 Data Recombination for Neural Semantic Parsing Robin Jia, Percy Liang 9999
45 Natural Language Processing Jacob Eisenstein 1181
46 Joint Models for NLP Yue Zhang 1311
47 Gimli: open source and high-performance biomedical name recognition David Campos, Sergio Matos, Jose Oliveira 9999
48 Strategies for Training Large Vocabulary Neural Language Models Wenlin Chen, David Grangier, Michael Auli 9999
49 Globally Normalized Transition-Based Neural Networks Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessan... 9999
50 What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment Hongyuan Mei, Mohit Bansal, Matthew R. Walter 9999