GRACE (BBN): Low Resource Languages for Emergent Incidents (LORELEI)

Project funded by DARPA (LORELEI)
PI: Philip Resnik
coPI (PI while at Colorado): Jordan Boyd-Graber

The goal of the Low Resource Languages for Emergent Incidents (LORELEI) Program is to dramatically advance the state of computational linguistics and human language technology to enable rapid, low-cost development of capabilities for low-resource languages. With the understanding that even with perfect translation, there would still be too much material for analysts to use effectively, LORELEI research will not be focused solely on machine translation. While LORELEI technologies may include partial or fully automated speech recognition and/or machine translation, the overall goal will not be translating foreign language material into English but providing situational awareness by identifying elements of information in foreign language and English sources, such as topics, names, events, sentiment and relationships.

The UMD focused on improving representations for low resource langauges through using related languages and human interaction.

	Jordan Boyd-Graber Assistant Professor, Computer Science (UMD)
	Shi Feng PhD Student, Computer Science (UMD)
	Ting Hua Postdoc (JHU)
	Yoshinari Fujinuma PhD Student, Computer Science (Colorado)
	Weiwei Yang PhD Student, Computer Science (UMD)
	Mozhi Zhang PhD Student, Computer Science (UMD)

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• Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi, Stefanie Jegelka. What Can Neural Networks Reason About? ICLR, 2020.
• Mozhi Zhang, Yoshinari Fujinuma, and Jordan Boyd-Graber. Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification. Association for the Advancement of Artificial Intelligence, 2020. [Bibtex]
  
  

  @inproceedings{Zhang:Fujinuma:Boyd-Graber-2020,
  	Title = {Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification},
  	Author = {Mozhi Zhang and Yoshinari Fujinuma and Jordan Boyd-Graber},
  	Booktitle = {Association for the Advancement of Artificial Intelligence},
  	Year = {2020},
  	Location = {New York, New York},
  	Url = {https://arxiv.org/abs/1812.09617},
  }
  

• Yoshinari Fujinuma, Michael Paul, and Jordan Boyd-Graber. A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity. Association for Computational Linguistics, 2019. [Bibtex]
  
  

  @inproceedings{Fujinuma:Paul:Boyd-Graber-2019,
  	Title = {A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity},
  	Author = {Yoshinari Fujinuma and Michael Paul and Jordan Boyd-Graber},
  	Booktitle = {Association for Computational Linguistics},
  	Year = {2019},
  	Location = {Florence, Italy},
  	Url = {http://cs.umd.edu/~jbg//docs/2019_acl_modularity.pdf},
  }
  

• Mozhi Zhang, Keyulu Xu, Ken-ichi Kawarabayashi, Stefanie Jegelka, and Jordan Boyd-Graber. Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization. Association for Computational Linguistics, 2019. [Preprint] [Bibtex]
  
  

  @inproceedings{Zhang:Xu:Kawarabayashi:Jegelka:Boyd-Graber-2019,
  	Author = {Mozhi Zhang and Keyulu Xu and Ken-ichi Kawarabayashi and Stefanie Jegelka and Jordan Boyd-Graber},
  	Title = {Are Girls Neko or Sh{\=o}jo? {C}ross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization},
  	Booktitle = {Association for Computational Linguistics},
  	Year = {2019},
  	Location = {Florence, Italy},
  	Url = {http://cs.umd.edu/~jbg//docs/2019_acl_clwe.pdf},
  }
  

• Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora. Empirical Methods in Natural Language Processing, 2019. [Bibtex]
  
  

  @inproceedings{Yang:Boyd-Graber:Resnik-2019,
  	Title = {A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora},
  	Booktitle = {Empirical Methods in Natural Language Processing},
  	Year = {2019},
  	Location = {Hong Kong, China},
  	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
  	Url = {http://cs.umd.edu/~jbg//docs/2019_emnlp_mtm.pdf},
  }
  

• Shi Feng and Jordan Boyd-Graber. What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play. Intelligent User Interfaces, 2019. [Bibtex]
  
  

  @inproceedings{Feng:Boyd-Graber-2019,
  	Title = {What AI can do for me: Evaluating Machine Learning Interpretations in Cooperative Play},
  	Author = {Shi Feng and Jordan Boyd-Graber},
  	Booktitle = {Intelligent User Interfaces},
  	Year = {2019},
  	Location = {Los Angeles, CA},
  	Url = {http://cs.umd.edu/~jbg//docs/2019_iui_augment.pdf},
  }
  

  
  
• Shi Feng, Eric Wallace, and Jordan Boyd-Graber. Interpreting Neural Networks with Nearest Neighbors. EMNLP Workshop on BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2018. [Bibtex]
  
  

  @inproceedings{Feng:Wallace:Boyd-Graber-2018,
  	Title = {Interpreting Neural Networks with Nearest Neighbors},
  	Author = {Shi Feng and Eric Wallace and Jordan Boyd-Graber},
  	Booktitle = {EMNLP Workshop on BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP},
  	Year = {2018},
  	Location = {Brussels, Belgium},
  	Url = {http://aclweb.org/anthology/W18-5416},
  }
  

• Shi Feng, Eric Wallace, Alvin Grissom II, Pedro Rodriguez, Mohit Iyyer, and Jordan Boyd-Graber. Pathologies of Neural Models Make Interpretation Difficult. Empirical Methods in Natural Language Processing, 2018. [Blog Post] [Bibtex]
  
  

  @inproceedings{Feng:Wallace:II:Rodriguez:Iyyer:Boyd-Graber-2018,
  	Title = {Pathologies of Neural Models Make Interpretation Difficult},
  	Author = {Shi Feng and Eric Wallace and Alvin Grissom II and Pedro Rodriguez and Mohit Iyyer and Jordan Boyd-Graber},
  	Booktitle = {Empirical Methods in Natural Language Processing},
  	Year = {2018},
  	Location = {Brussels, Belgium},
  	Url = {http://cs.umd.edu/~jbg//docs/2018_emnlp_rs.pdf},
  }
  

  
  
• Michelle Yuan, Benjamin Van Durme, and Jordan Boyd-Graber. Multilingual Anchoring: Interactive Topic Modeling and Alignment Across Languages. Neural Information Processing Systems, 2018. [Code] [Bibtex]
  
  

  @inproceedings{Yuan:Van-Durme:Boyd-Graber-2018,
  	Title = {Multilingual Anchoring: Interactive Topic Modeling and Alignment  Across Languages},
  	Author = {Michelle Yuan and Benjamin {Van Durme} and Jordan Boyd-Graber},
  	Booktitle = {Neural Information Processing Systems},
  	Year = {2018},
  	Location = {Montreal, Quebec},
  	Url = {http://cs.umd.edu/~jbg//docs/2018_neurips_mtanchor.pdf},
  }
  

  
  
• Shudong Hao, Michael J. Paul, and Jordan Boyd-Graber. Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages. North American Association for Computational Linguistics, 2018. [Bibtex]
  
  

  @inproceedings{Hao:Paul:Boyd-Graber-2018,
  	Title = {Lessons from the Bible on Modern Topics: Multilingual Topic Model Evaluation on Low-Resource Languages},
  	Author = {Shudong Hao and Michael J. Paul and Jordan Boyd-Graber},
  	Booktitle = {North American Association for Computational Linguistics},
  	Year = {2018},
  	Location = {New Orleans, LA},
  	Url = {http://cs.umd.edu/~jbg//docs/2018_naacl_mltm_eval.pdf},
  }
  

  
  
• Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Adapting Topic Models using Lexical Associations with Tree Priors. Empirical Methods in Natural Language Processing, 2017. [Bibtex]
  
  

  @inproceedings{Yang:Boyd-Graber:Resnik-2017,
  	Title = {Adapting Topic Models using Lexical Associations with Tree Priors},
  	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
  	Booktitle = {Empirical Methods in Natural Language Processing},
  	Year = {2017},
  	Location = {Copenhagen, Denmark},
  	Url = {http://cs.umd.edu/~jbg//docs/2017_emnlp_tree_prior.pdf},
  }
  

• Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. A Discriminative Topic Model using Document Network Structure. Association for Computational Linguistics, 2016. [Supplement] [Bibtex]
  
  

  @inproceedings{Yang:Boyd-Graber:Resnik-2016,
  	Title = {A Discriminative Topic Model using Document Network Structure},
  	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
  	Booktitle = {Association for Computational Linguistics},
  	Year = {2016},
  	Location = {Berlin, Brandenburg},
  	Url = {http://cs.umd.edu/~jbg//docs/2016_acl_docblock.pdf},
  }
  

  
  
• Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors. Mid-Atlantic Student Colloquium on Speech, Language, and Learning, 2016. [Bibtex]
  
  

  @inproceedings{Yang:Boyd-Graber:Resnik-2016,
  	Title = {Birds of a Feather in the Same Nest: A Discriminative Topic Model using Block-based Priors},
  	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
  	Booktitle = {Mid-Atlantic Student Colloquium on Speech, Language, and Learning},
  	Year = {2016},
  	Location = {Philadephia},
  }
  

• Weiwei Yang, Jordan Boyd-Graber, and Philip Resnik. Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors. Empirical Methods in Natural Language Processing, 2015. [Bibtex]
  
  

  @inproceedings{Yang:Boyd-Graber:Resnik-2015,
  	Title = {Birds of a Feather Linked Together: A Discriminative Topic Model using Link-based Priors},
  	Url = {http://cs.umd.edu/~jbg//docs/2015_emnlp_hinge_link.pdf},
  	Author = {Weiwei Yang and Jordan Boyd-Graber and Philip Resnik},
  	Booktitle = {Empirical Methods in Natural Language Processing},
  	Year = {2015},
  	Location = {Lisbon, Portugal},
  }
  

Acknowledgments

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the researchers and do not necessarily reflect the views of the sponsor.