 | 2011 |
| 16 |  | Marco Kuhlmann,
Carlos Gómez-Rodríguez,
Giorgio Satta:
Dynamic Programming Algorithms for Transition-Based Dependency Parsers.
ACL 2011: 673-682 |
| 15 |  | Alexander Koller,
Marco Kuhlmann:
A Generalized View on Parsing and Translation.
IWPT 2011: 2-13 |
| 2010 |
| 14 |  | Marco Kuhlmann:
Dependency Structures and Lexicalized Grammars An Algebraic Approach
Springer 2010 |
| 13 |  | Marco Kuhlmann,
Alexander Koller,
Giorgio Satta:
The Importance of Rule Restrictions in CCG.
ACL 2010: 534-543 |
| 12 |  | Carlos Gómez-Rodríguez,
Marco Kuhlmann,
Giorgio Satta:
Efficient Parsing of Well-Nested Linear Context-Free Rewriting Systems.
HLT-NAACL 2010: 276-284 |
| 11 |  | Marco Kuhlmann:
Dependency structures and lexicalized grammars: an algebraic approach.
Saarland University 2010: 1-137 |
| 2009 |
| 10 |  | Alexander Koller,
Marco Kuhlmann:
Dependency Trees and the Strong Generative Capacity of CCG.
EACL 2009: 460-468 |
| 9 |  | Marco Kuhlmann,
Giorgio Satta:
Treebank Grammar Techniques for Non-Projective Dependency Parsing.
EACL 2009: 478-486 |
| 8 |  | Carlos Gómez-Rodríguez,
Marco Kuhlmann,
Giorgio Satta,
David J. Weir:
Optimal Reduction of Rule Length in Linear Context-Free Rewriting Systems.
HLT-NAACL 2009: 539-547 |
| 7 |  | Joakim Nivre,
Marco Kuhlmann,
Johan Hall:
An Improved Oracle for Dependency Parsing with Online Reordering.
IWPT 2009: 73-76 |
| 6 |  | Marisa Ferrara Boston,
John T. Hale,
Marco Kuhlmann:
Dependency Structures Derived from Minimalist Grammars.
MOL 2009: 1-12 |
| 2008 |
| 5 |  | Marco Kuhlmann,
Joachim Niehren:
Logics and Automata for Totally Ordered Trees.
RTA 2008: 217-231 |
| 4 |  | Marco Kuhlmann:
Ogden's Lemma for Regular Tree Languages
CoRR abs/0810.4249: (2008) |
| 2007 |
| 3 |  | Marco Kuhlmann,
Mathias Möhl:
Mildly Context-Sensitive Dependency Languages.
ACL 2007 |
| 2006 |
| 2 |  | Marco Kuhlmann,
Joakim Nivre:
Mildly Non-Projective Dependency Structures.
ACL 2006 |
| 2004 |
| 1 |  | Ralph Debusmann,
Denys Duchier,
Marco Kuhlmann:
Multi-dimensional Graph Configuration for Natural Language Processing.
CSLP 2004: 104-120 |