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20152021
most citedYara Parser: A Fast and Accurate Dependency Parser

71 citations · 89 across the 7 of their papers we have counts for

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10 papers · 1 filter

cs.CL2021

"Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks

Mohammad Sadegh Rasooli, Chris Callison-Burch, Derry Tanti Wijaya

We present a simple but effective approach for leveraging Wikipedia for neural machine translation as well as cross-lingual tasks of image captioning and dependency parsing without…

cs.CL20201 cited

Automatic Standardization of Colloquial Persian

Mohammad Sadegh Rasooli, Farzane Bakhtyari, Fatemeh Shafiei +2

The Iranian Persian language has two varieties: standard and colloquial. Most natural language processing tools for Persian assume that the text is in standard form: this assumptio…

cs.CL2020

ParsiNLU: A Suite of Language Understanding Challenges for Persian

Daniel Khashabi, Arman Cohan, Siamak Shakeri +22

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich l…

cs.CL20205 cited

The Persian Dependency Treebank Made Universal

Mohammad Sadegh Rasooli, Pegah Safari, Amirsaeid Moloodi +1

We describe an automatic method for converting the Persian Dependency Treebank (Rasooli et al, 2013) to Universal Dependencies. This treebank contains 29107 sentences. Our experime…

cs.CL20201 cited

Mutlitask Learning for Cross-Lingual Transfer of Semantic Dependencies

Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab

We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available. We leverage a multitask lear…

cs.CL20191 cited

Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles

Maryam Aminian, Mohammad Sadegh Rasooli, Mona Diab

We describe a transfer method based on annotation projection to develop a dependency-based semantic role labeling system for languages for which no supervised linguistic informatio…