Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network
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Eyal Shnarch | Noam Slonim | Ranit Aharonov | Leshem Choshen | Lena Dankin | Martin Gleize | Guy Moshkowich | R. Aharonov | N. Slonim | Lena Dankin | Eyal Shnarch | Leshem Choshen | Martin Gleize | Guy Moshkowich
[1] Sarit Kraus,et al. Providing Arguments in Discussions on the Basis of the Prediction of Human Argumentative Behavior , 2016, ACM Trans. Interact. Intell. Syst..
[2] Wei Chu,et al. Preference learning with Gaussian processes , 2005, ICML.
[3] Tie-Yan Liu,et al. Learning to rank: from pairwise approach to listwise approach , 2007, ICML '07.
[4] Benno Stein,et al. Argumentation Quality Assessment: Theory vs. Practice , 2017, ACL.
[5] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[6] Jacob Cohen. A Coefficient of Agreement for Nominal Scales , 1960 .
[7] B. J. Fogg,et al. A behavior model for persuasive design , 2009, Persuasive '09.
[8] T. Brock,et al. Journal of Personality and Social Psychology the Role of Transportation in the Persuasiveness of Public Narratives Text Quality Individual Differences and Situational Influences Transportation Scale Items Gender Differences Discriminant Validation: Need for Cognition Effect of Text Manipulation Beli , 2022 .
[9] Cristian Danescu-Niculescu-Mizil,et al. Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions , 2016, WWW.
[10] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[11] J. A. Blair,et al. Logical Self-Defense , 1977 .
[12] O. Oha. Fallacies , 2005 .
[13] Chris Callison-Burch,et al. Seeing Things from a Different Angle:Discovering Diverse Perspectives about Claims , 2019, NAACL.
[14] Beate Baltes,et al. Assessing Quality of Critical Thought in Online Discussion , 2009 .
[15] Brent Brossmann. Fallacies and Argument Appraisal , 2006 .
[16] M. Pigliucci,et al. The Fake, the Flimsy, and the Fallacious: Demarcating Arguments in Real Life , 2015 .
[17] Gert R. G. Lanckriet,et al. Metric Learning to Rank , 2010, ICML.
[18] Aaron C. Courville,et al. Recurrent Batch Normalization , 2016, ICLR.
[19] Kathleen McKeown,et al. Persuasive Influence Detection: The Role of Argument Sequencing , 2018, AAAI.
[20] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[21] Iryna Gurevych,et al. Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM , 2016, ACL.
[22] Gregory N. Hullender,et al. Learning to rank using gradient descent , 2005, ICML.
[23] Iryna Gurevych,et al. Exploiting Debate Portals for Semi-Supervised Argumentation Mining in User-Generated Web Discourse , 2015, EMNLP.
[24] Christopher J. C. Burges,et al. From RankNet to LambdaRank to LambdaMART: An Overview , 2010 .
[25] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[26] A. Vinokur,et al. Persuasive argumentation and social comparison as determinants of attitude polarization , 1977 .
[27] B. J. Fogg,et al. Persuasive computers: perspectives and research directions , 1998, CHI.
[28] Claire Cardie,et al. Exploring the Role of Prior Beliefs for Argument Persuasion , 2018, NAACL.
[29] B. J. Fogg,et al. Persuasive technology: using computers to change what we think and do , 2002, UBIQ.
[30] Iryna Gurevych,et al. Parsing Argumentation Structures in Persuasive Essays , 2016, CL.
[31] Rajeev Motwani,et al. The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.
[32] Iryna Gurevych,et al. Annotating Argument Components and Relations in Persuasive Essays , 2014, COLING.
[33] D. O’Keefe. Conviction, Persuasion, and Argumentation: Untangling the Ends and Means of Influence , 2012 .
[34] Iryna Gurevych,et al. Finding Convincing Arguments Using Scalable Bayesian Preference Learning , 2018, TACL.
[35] Vincent Ng,et al. Why Can't You Convince Me? Modeling Weaknesses in Unpersuasive Arguments , 2017, IJCAI.
[36] Iryna Gurevych,et al. What makes a convincing argument? Empirical analysis and detecting attributes of convincingness in Web argumentation , 2016, EMNLP.
[37] Bart Verheij,et al. Handbook of Argumentation Theory , 1987 .
[38] Anna Rumshisky,et al. Towards Debate Automation: a Recurrent Model for Predicting Debate Winners , 2017, EMNLP.
[39] Alessandro Moschitti,et al. Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks , 2015, SIGIR.
[40] Benno Stein,et al. Using Argument Mining to Assess the Argumentation Quality of Essays , 2016, COLING.
[41] Eyal Shnarch,et al. Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining , 2018, ACL.
[42] Noam Slonim,et al. A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics , 2014, ArgMining@ACL.
[43] Noam Slonim,et al. Context Dependent Claim Detection , 2014, COLING.
[44] Debanjan Ghosh,et al. Coarse-grained Argumentation Features for Scoring Persuasive Essays , 2016, ACL.
[45] Paolo Torroni,et al. Argumentation Mining , 2016, ACM Trans. Internet Techn..
[46] Mitesh M. Khapra,et al. Show Me Your Evidence - an Automatic Method for Context Dependent Evidence Detection , 2015, EMNLP.