Search Results for author: Mounica Maddela

Found 12 papers, 8 papers with code

EntSUM: A Data Set for Entity-Centric Extractive Summarization

1 code implementation ACL 2022 Mounica Maddela, Mayank Kulkarni, Daniel Preotiuc-Pietro

Controllable summarization aims to provide summaries that take into account user-specified aspects and preferences to better assist them with their information need, as opposed to the standard summarization setup which build a single generic summary of a document. We introduce a human-annotated data set EntSUM for controllable summarization with a focus on named entities as the aspects to control. We conduct an extensive quantitative analysis to motivate the task of entity-centric summarization and show that existing methods for controllable summarization fail to generate entity-centric summaries.

Extractive Summarization

Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts

no code implementations6 Jul 2023 Mounica Maddela, Megan Ung, Jing Xu, Andrea Madotto, Heather Foran, Y-Lan Boureau

Many cognitive approaches to well-being, such as recognizing and reframing unhelpful thoughts, have received considerable empirical support over the past decades, yet still lack truly widespread adoption in self-help format.

Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA

no code implementations23 May 2023 David Heineman, Yao Dou, Mounica Maddela, Wei Xu

Large language models (e. g., GPT-3. 5) are uniquely capable of producing highly rated text simplification, yet current human evaluation methods fail to provide a clear understanding of systems' specific strengths and weaknesses.

Text Simplification

LENS: A Learnable Evaluation Metric for Text Simplification

1 code implementation19 Dec 2022 Mounica Maddela, Yao Dou, David Heineman, Wei Xu

Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation.

Machine Translation Text Simplification

EntSUM: A Data Set for Entity-Centric Summarization

1 code implementation5 Apr 2022 Mounica Maddela, Mayank Kulkarni, Daniel Preotiuc-Pietro

Our analysis and results show the challenging nature of this task and of the proposed data set.

BiSECT: Learning to Split and Rephrase Sentences with Bitexts

1 code implementation EMNLP 2021 Joongwon Kim, Mounica Maddela, Reno Kriz, Wei Xu, Chris Callison-Burch

We categorize examples in our corpus, and use these categories in a novel model that allows us to target specific regions of the input sentence to be split and edited.

Machine Translation Split and Rephrase +1

Controllable Text Simplification with Explicit Paraphrasing

no code implementations NAACL 2021 Mounica Maddela, Fernando Alva-Manchego, Wei Xu

Text Simplification improves the readability of sentences through several rewriting transformations, such as lexical paraphrasing, deletion, and splitting.

Data Augmentation Text Simplification

Neural CRF Model for Sentence Alignment in Text Simplification

1 code implementation ACL 2020 Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, Wei Xu

The success of a text simplification system heavily depends on the quality and quantity of complex-simple sentence pairs in the training corpus, which are extracted by aligning sentences between parallel articles.

Semantic Similarity Semantic Textual Similarity +1

Code and Named Entity Recognition in StackOverflow

2 code implementations ACL 2020 Jeniya Tabassum, Mounica Maddela, Wei Xu, Alan Ritter

We also present the SoftNER model which achieves an overall 79. 10 F$_1$ score for code and named entity recognition on StackOverflow data.

named-entity-recognition Named Entity Recognition +1

Multi-task Pairwise Neural Ranking for Hashtag Segmentation

1 code implementation ACL 2019 Mounica Maddela, Wei Xu, Daniel Preoţiuc-Pietro

Hashtags are often employed on social media and beyond to add metadata to a textual utterance with the goal of increasing discoverability, aiding search, or providing additional semantics.

Sentiment Analysis

A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification

1 code implementation EMNLP 2018 Mounica Maddela, Wei Xu

Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment.

Lexical Simplification

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