no code implementations • EMNLP 2020 • Prithviraj Sen, Marina Danilevsky, Yunyao Li, Siddhartha Brahma, Matthias Boehm, Laura Chiticariu, Rajasekar Krishnamurthy
Our user studies confirm that the learned LEs are explainable and capture domain semantics.
1 code implementation • EMNLP 2020 • Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, Noam Slonim
Here, we present a large-scale empirical study on active learning techniques for BERT-based classification, addressing a diverse set of AL strategies and datasets.
no code implementations • 15 Nov 2023 • Ankita Gupta, Chulaka Gunasekara, Hui Wan, Jatin Ganhotra, Sachindra Joshi, Marina Danilevsky
We find that both fine-tuned and instruction-tuned models are affected by input variations, with the latter being more susceptible, particularly to dialogue-level perturbations.
no code implementations • 26 Aug 2023 • Hui Wan, Hongkang Li, Songtao Lu, Xiaodong Cui, Marina Danilevsky
The integration of external personalized context information into document-grounded conversational systems has significant potential business value, but has not been well-studied.
no code implementations • 3 Jan 2023 • Rudra Murthy V, Riyaz Bhat, Chulaka Gunasekara, Siva Sankalp Patel, Hui Wan, Tejas Indulal Dhamecha, Danish Contractor, Marina Danilevsky
In this paper we explore the task of modeling semi-structured object sequences; in particular, we focus our attention on the problem of developing a structure-aware input representation for such sequences.
1 code implementation • 12 Oct 2022 • Ishan Jindal, Alexandre Rademaker, Khoi-Nguyen Tran, Huaiyu Zhu, Hiroshi Kanayama, Marina Danilevsky, Yunyao Li
In this paper, we address key practical issues with existing evaluation scripts and propose a more strict SRL evaluation metric PriMeSRL.
1 code implementation • 2 Aug 2022 • Eyal Shnarch, Alon Halfon, Ariel Gera, Marina Danilevsky, Yannis Katsis, Leshem Choshen, Martin Santillan Cooper, Dina Epelboim, Zheng Zhang, Dakuo Wang, Lucy Yip, Liat Ein-Dor, Lena Dankin, Ilya Shnayderman, Ranit Aharonov, Yunyao Li, Naftali Liberman, Philip Levin Slesarev, Gwilym Newton, Shila Ofek-Koifman, Noam Slonim, Yoav Katz
Text classification can be useful in many real-world scenarios, saving a lot of time for end users.
1 code implementation • Findings (ACL) 2022 • Ayush Maheshwari, KrishnaTeja Killamsetty, Ganesh Ramakrishnan, Rishabh Iyer, Marina Danilevsky, Lucian Popa
These LFs, in turn, have been used to generate a large amount of additional noisy labeled data, in a paradigm that is now commonly referred to as data programming.
no code implementations • NAACL 2021 • 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
Contracts are arguably the most important type of business documents.
no code implementations • 29 Jan 2021 • Soya Park, April Wang, Ban Kawas, Q. Vera Liao, David Piorkowski, Marina Danilevsky
Data scientists face a steep learning curve in understanding a new domain for which they want to build machine learning (ML) models.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, Prithviraj Sen
Recent years have seen important advances in the quality of state-of-the-art models, but this has come at the expense of models becoming less interpretable.
1 code implementation • CONLL 2018 • Min Li, Marina Danilevsky, Sara Noeman, Yunyao Li
Phonetic similarity algorithms identify words and phrases with similar pronunciation which are used in many natural language processing tasks.
no code implementations • NAACL 2018 • Laura Chiticariu, Marina Danilevsky, Yunyao Li, Frederick Reiss, Huaiyu Zhu
The rise of enterprise applications over unstructured and semi-structured documents poses new challenges to text understanding systems across multiple dimensions.
no code implementations • COLING 2016 • Alan Akbik, Laura Chiticariu, Marina Danilevsky, Yonas Kbrom, Yunyao Li, Huaiyu Zhu
We present PolyglotIE, a web-based tool for developing extractors that perform Information Extraction (IE) over multilingual data.
no code implementations • 11 Apr 2014 • Joshua Hailpern, Niranjan Damera Venkata, Marina Danilevsky
Results from this experiment show that one of our approaches strongly outperforms the baselines and alternatives.
no code implementations • 3 Jun 2013 • Marina Danilevsky, Chi Wang, Nihit Desai, Jingyi Guo, Jiawei Han
We introduce KERT (Keyphrase Extraction and Ranking by Topic), a framework for topical keyphrase generation and ranking.