52 citations · 66 across the 11 of their papers we have counts for
12 papers · 1 filter
BLESS: Benchmarking Large Language Models on Sentence Simplification
Tannon Kew, Alison Chi, Laura Vásquez-Rodríguez +4
We present BLESS, a comprehensive performance benchmark of the most recent state-of-the-art large language models (LLMs) on the task of text simplification (TS). We examine how wel…
Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
Mounica Maddela, Megan Ung, Jing Xu +3
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 tr…
Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA
David Heineman, Yao Dou, Mounica Maddela +1
Large language models (e.g., GPT-4) are uniquely capable of producing highly rated text simplification, yet current human evaluation methods fail to provide a clear understanding o…
LENS: A Learnable Evaluation Metric for Text Simplification
Mounica Maddela, Yao Dou, David Heineman +1
Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human eval…
EntSUM: A Data Set for Entity-Centric Summarization
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…
BiSECT: Learning to Split and Rephrase Sentences with Bitexts
Joongwon Kim, Mounica Maddela, Reno Kriz +2
An important task in NLP applications such as sentence simplification is the ability to take a long, complex sentence and split it into shorter sentences, rephrasing as necessary.…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
Controllable Text Simplification with Explicit Paraphrasing
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. Current simplification s…
Neural CRF Model for Sentence Alignment in Text Simplification
Chao Jiang, Mounica Maddela, Wuwei Lan +2
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 sen…
Code and Named Entity Recognition in StackOverflow
Jeniya Tabassum, Mounica Maddela, Wei Xu +1
There is an increasing interest in studying natural language and computer code together, as large corpora of programming texts become readily available on the Internet. For example…
Multi-task Pairwise Neural Ranking for Hashtag Segmentation
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 se…
A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification
Mounica Maddela, Wei Xu
Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity…