L. Venkata Subramaniam

Also published as: L V Subramaniam, L Venkata Subramaniam, L. V. Subramaniam


2022

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Zero-shot Entity Linking with Less Data
G P Shrivatsa Bhargav | Dinesh Khandelwal | Saswati Dana | Dinesh Garg | Pavan Kapanipathi | Salim Roukos | Alexander Gray | L Venkata Subramaniam
Findings of the Association for Computational Linguistics: NAACL 2022

Entity Linking (EL) maps an entity mention in a natural language sentence to an entity in a knowledge base (KB). The Zero-shot Entity Linking (ZEL) extends the scope of EL to unseen entities at the test time without requiring new labeled data. BLINK (BERT-based) is one of the SOTA models for ZEL. Interestingly, we discovered that BLINK exhibits diminishing returns, i.e., it reaches 98% of its performance with just 1% of the training data and the remaining 99% of the data yields only a marginal increase of 2% in the performance. While this extra 2% gain makes a huge difference for downstream tasks, training BLINK on large amounts of data is very resource-intensive and impractical. In this paper, we propose a neuro-symbolic, multi-task learning approach to bridge this gap. Our approach boosts the BLINK’s performance with much less data by exploiting an auxiliary information about entity types. Specifically, we train our model on two tasks simultaneously - entity linking (primary task) and hierarchical entity type prediction (auxiliary task). The auxiliary task exploits the hierarchical structure of entity types. Our approach achieves superior performance on ZEL task with significantly less training data. On four different benchmark datasets, we show that our approach achieves significantly higher performance than SOTA models when they are trained with just 0.01%, 0.1%, or 1% of the original training data. Our code is available at https://github.com/IBM/NeSLET.

2017

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SemTagger: A Novel Approach for Semantic Similarity Based Hashtag Recommendation on Twitter
Kuntal Dey | Ritvik Shrivastava | Saroj Kaushik | L Venkata Subramaniam
Proceedings of the 14th International Conference on Natural Language Processing (ICON-2017)

2013

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An Empirical Assessment of Contemporary Online Media in Ad-Hoc Corpus Creation for Social Events
Kanika Narang | Seema Nagar | Sameep Mehta | L V Subramaniam | Kuntal Dey
Proceedings of the Sixth International Joint Conference on Natural Language Processing

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NLP for uncertain data at scale
Sameep Mehta | L. V. Subramaniam
NAACL HLT 2013 Tutorial Abstracts

2011

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Using Text Reviews for Product Entity Completion
Mrinmaya Sachan | Tanveer Faruquie | L. V. Subramaniam | Mukesh Mohania
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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Automatically Generating Term Frequency Induced Taxonomies
Karin Murthy | Tanveer A Faruquie | L Venkata Subramaniam | Hima Prasad K | Mukesh Mohania
Proceedings of the ACL 2010 Conference Short Papers

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Unsupervised cleansing of noisy text
Danish Contractor | Tanveer A. Faruquie | L. Venkata Subramaniam
Coling 2010: Posters

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Handling Noisy Queries in Cross Language FAQ Retrieval
Danish Contractor | Govind Kothari | Tanveer Faruquie | L. V. Subramaniam | Sumit Negi
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

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Noisy Text Analytics
L. Venkata Subramaniam
NAACL HLT 2010 Tutorial Abstracts

2009

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SMS based Interface for FAQ Retrieval
Govind Kothari | Sumit Negi | Tanveer A. Faruquie | Venkatesan T. Chakaravarthy | L. Venkata Subramaniam
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

2007

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Automatic Identification of Important Segments and Expressions for Mining of Business-Oriented Conversations at Contact Centers
Hironori Takeuchi | L Venkata Subramaniam | Tetsuya Nasukawa | Shourya Roy
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

2006

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Automatic Generation of Domain Models for Call-Centers from Noisy Transcriptions
Shourya Roy | L Venkata Subramaniam
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics