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CoNLL Shared Task Session, Prague, June 30, 2007


Introduction (Joakim Nivre)


Single Malt or Blended? A Study in Multilingual Parser Optimization
Johan Hall, Jens Nilsson, Joakim Nivre, Gülsen Eryigit, Beáta Megyesi, Mattias Nilsson and Markus Saers


Probabilistic Parsing Action Models for Multi-Lingual Dependency Parsing
Xiangyu Duan, Jun Zhao and Bo Xu


Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model
Ivan Titov and James Henderson


Multilingual Dependency Parsing Using Global Features
Tetsuji Nakagawa


Experiments with a Higher-Order Projective Dependency Parser
Xavier Carreras


Log-Linear Models of Non-Projective Trees, k-best MST Parsing and Tree-Ranking
Keith Hall, Jiri Havelka and David A. Smith




Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
Kenji Sagae and JunâÄôichi Tsujii


Frustratingly Hard Domain Adaptation for Dependency Parsing
Mark Dredze, John Blitzer, Partha Pratim Talukdar, Kuzman Ganchev, João Graca and Fernando Pereira


Analysis (Sandra Kübler and Ryan McDonald)



Additional Papers

Multilingual Dependency Parsing and Domain Adaptation using DeSR
Giuseppe Attardi, Felice DellâÄôOrletta, Maria Simi, Atanas Chanev and Massimiliano Ciaramita

Hybrid Ways to Improve Domain Independence in an ML Dependency Parser
Eckhard Bick

A Constraint Satisfaction Approach to Dependency Parsing
Sander Canisius and Erik Tjong Kim Sang

A Two-Stage Parser for Multilingual Dependency Parsing
Wenliang Chen, Yujie Zhang and Hitoshi Isahara

Incremental Dependency Parsing Using Online Learning
Richard Johansson and Pierre Nugues

Online Learning for Deterministic Dependency Parsing
Prashanth Reddy Mannem

Covington Variations
Svetoslav Marinov

A Multilingual Dependency Analysis System Using Online Passive-Aggressive LearningLe-Minh Nguyen, Akira Shimazu, Phuong-Thai Nguyen and Xuan-Hieu Phan

Global Learning of Labeled Dependency Trees
Michael Schiehlen and Kristina Spranger

Pro3Gres Parser in the CoNLL Domain Adaptation Shared Task
Gerold Schneider, Kaarel Kaljurand, Fabio Rinaldi and Tobias Kuhn

Structural Correspondence Learning for Dependency Parsing
Nobuyuki Shimizu and Hiroshi Nakagawa

Adapting the RASP System for the CoNLL07 Domain-Adaptation Task
Rebecca Watson and Ted Briscoe

Multilingual Deterministic Dependency Parsing Framework using Modified Finite Newton Method Support Vector Machines
Yu-Chieh Wu, Jie-Chi Yang and Yue-Shi Lee

SessionProgram (last edited 2007-05-30 07:25:59 by Joakim Nivre)