8 citations · 19 across the 10 of their papers we have counts for
10 papers
Discourse-Driven Evaluation: Unveiling Factual Inconsistency in Long Document Summarization
Yang Zhong, Diane Litman
Detecting factual inconsistency for long document summarization remains challenging, given the complex structure of the source article and long summary length. In this work, we stu…
AI-generated Essays: Characteristics and Implications on Automated Scoring and Academic Integrity
Yang Zhong, Jiangang Hao, Michael Fauss +2
The rapid advancement of large language models (LLMs) has enabled the generation of coherent essays, making AI-assisted writing increasingly common in educational and professional…
ReflectSumm: A Benchmark for Course Reflection Summarization
Yang Zhong, Mohamed Elaraby, Diane Litman +2
This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of ReflectSumm is to facilitate develo…
Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining
Zhexiong Liu, Mohamed Elaraby, Yang Zhong +1
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023. Th…
STRONG -- Structure Controllable Legal Opinion Summary Generation
Yang Zhong, Diane Litman
We propose an approach for the structure controllable summarization of long legal opinions that considers the argument structure of the document. Our approach involves using predic…
Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking
Mohamed Elaraby, Yang Zhong, Diane Litman
We propose a simple approach for the abstractive summarization of long legal opinions that considers the argument structure of the document. Legal opinions often contain complex an…
Computing and Exploiting Document Structure to Improve Unsupervised Extractive Summarization of Legal Case Decisions
Yang Zhong, Diane Litman
Though many algorithms can be used to automatically summarize legal case decisions, most fail to incorporate domain knowledge about how important sentences in a legal decision rela…
Modeling Intensification for Sign Language Generation: A Computational Approach
Mert İnan, Yang Zhong, Sabit Hassan +2
End-to-end sign language generation models do not accurately represent the prosody in sign language. A lack of temporal and spatial variations leads to poor-quality generated prese…
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…
Discourse Level Factors for Sentence Deletion in Text Simplification
Yang Zhong, Chao Jiang, Wei Xu +1
This paper presents a data-driven study focusing on analyzing and predicting sentence deletion -- a prevalent but understudied phenomenon in document simplification -- on a large E…