Papers by Laura Chiticariu
Learning Explainable Linguistic Expressions with Neural Inductive Logic Programming for Sentence Classification (2020.emnlp-main)
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Prithviraj Sen, Marina Danilevsky, Yunyao Li, Siddhartha Brahma, Matthias Boehm, Laura Chiticariu, Rajasekar Krishnamurthy
| Challenge: | Existing approaches to explain models are difficult to interpret and have undesirable biases. |
| Approach: | They propose a neural network architecture for learning transparent sentences . they use linguistic expressions built on top of predicates extracted using shallow natural language understanding . |
| Outcome: | The proposed model outperforms statistical relational learning and other neuro-symbolic methods and performs better than black-box recurrent neural networks. |
SystemT: Declarative Text Understanding for Enterprise (N18-3)
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| Challenge: | a growing number of enterprise applications are relying on text understanding systems to understand information in unstructured and semi-structured forms. |
| Approach: | They propose a declarative text understanding system that addresses these challenges . they summarize the impact of SystemT on business and education . |
| Outcome: | The system addresses the challenges of enterprise text understanding systems . it has been deployed in a wide range of enterprise applications . |
Domain-Aware Dependency Parsing for Questions (2021.findings-acl)
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| Challenge: | Pre-trained parsers perform poorly on domain-specific questions, a paper argues . retraining parser with domain- specific questions is expensive, as these require linguistic expertise. |
| Approach: | They propose an automatic labeled domain question generation framework leveraging domain knowledge and seed domain questions. |
| Outcome: | The proposed framework improves state-of-the-art parsers on domain questions. |
Development of an Enterprise-Grade Contract Understanding System (2021.naacl-industry)
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Arvind Agarwal, Laura Chiticariu, Poornima Chozhiyath Raman, Marina Danilevsky, Diman Ghazi, Ankush Gupta, Shanmukha Guttula, Yannis Katsis, Rajasekar Krishnamurthy, Yunyao Li, Shubham Mudgal, Vitobha Munigala, Nicholas Phan, Dhaval Sonawane, Sneha Srinivasan, Sudarshan R. Thitte, Mitesh Vasa, Ramiya Venkatachalam, Vinitha Yaski, Huaiyu Zhu
| Challenge: | Currently, legal contract review remains an expensive and arduous process. |
| Approach: | They describe a commercial system designed and deployed for contract understanding that enables legal professionals to review contracts. |
| Outcome: | The proposed system is used by a wide range of enterprise users and solves three major challenges. |