M
Mounica Maddela
Publications - 20
Citations - 397
Mounica Maddela is an academic researcher. The author has contributed to research in topics: Computer science & Text simplification. The author has an hindex of 7, co-authored 13 publications receiving 154 citations.
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Proceedings ArticleDOI
Neural CRF Model for Sentence Alignment in Text Simplification
TL;DR: This paper proposed a neural CRF alignment model which not only leverages the sequential nature of sentences in parallel documents, but also utilizes a neural sentence pair model to capture semantic similarity for text simplification.
Proceedings ArticleDOI
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
Mounica Maddela,Wei Xu +1 more
TL;DR: This work creates a human-rated word-complexity lexicon of 15,000 English words and proposes a novel neural readability ranking model with a Gaussian-based feature vectorization layer that utilizes these human ratings to measure the complexity of any given word or phrase.
Proceedings ArticleDOI
Controllable Text Simplification with Explicit Paraphrasing
TL;DR: A novel hybrid approach is proposed that leverages linguistically-motivated rules for splitting and deletion, and couples them with a neural paraphrasing model to produce varied rewriting styles and establishes a new state-of-the-art for the task.
Posted Content
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics.
Sebastian Gehrmann,Tosin P. Adewumi,Karmanya Aggarwal,Pawan Sasanka Ammanamanchi,Aremu Anuoluwapo,Antoine Bosselut,Khyathi Raghavi Chandu,Miruna Clinciu,Dipanjan Das,Kaustubh Dhole,Wanyu Du,Esin Durmus,Ondřej Dušek,Chris Chinenye Emezue,Varun Gangal,Cristina Garbacea,Tatsunori Hashimoto,Yufang Hou,Yacine Jernite,Harsh Jhamtani,Yangfeng Ji,Shailza Jolly,Mihir Kale,Dhruv Kumar,Faisal Ladhak,Aman Madaan,Mounica Maddela,Khyati Mahajan,Saad Mahamood,Bodhisattwa Prasad Majumder,Pedro Henrique Martins,Angelina McMillan-Major,Simon Mille,Emiel van Miltenburg,Moin Nadeem,Shashi Narayan,Vitaly Nikolaev,Rubungo Andre Niyongabo,Salomey Osei,Ankur P. Parikh,Laura Perez-Beltrachini,Niranjan Ramesh Rao,Vikas Raunak,Juan Diego Rodriguez,Sashank Santhanam,João Sedoc,Thibault Sellam,Samira Shaikh,Anastasia Shimorina,Marco Antonio Sobrevilla Cabezudo,Hendrik Strobelt,Nishant Subramani,Wei Xu,Diyi Yang,Akhila Yerukola,Jiawei Zhou +55 more
TL;DR: GEM as discussed by the authors is a living benchmark for natural language generation (NLG), its Evaluation and Metrics, which provides an environment in which models can easily be applied to a wide set of tasks and in which evaluation strategies can be tested.
Posted Content
Code and Named Entity Recognition in StackOverflow
TL;DR: A new named entity recognition (NER) corpus for the computer programming domain is introduced, consisting of 15,372 sentences annotated with 20 fine-grained entity types, and the SoftNER model is presented, which incorporates a context-independent code token classifier with corpus-level features to improve the BERT-based tagging model.