13 citations · 23 across the 8 of their papers we have counts for
9 papers
Improving Argument Saliency Coverage in Small LLMs for Long Legal Opinion Summarization via Sequence-Level Distillation
Mohamed Elaraby, Ahmed Elhady, Diane Litman
We show that sequence-level distillation from a capable long-context teacher model is a simple, annotation-free, and data-efficient strategy for improving argument saliency coverag…
SynClaimEval: A Framework for Evaluating the Utility of Synthetic Data in Long-Context Claim Verification
Mohamed Elaraby, Jyoti Prakash Maheswari
Large Language Models (LLMs) with extended context windows promise direct reasoning over long documents, reducing the need for chunking or retrieval. Constructing annotated resourc…
ARC: Argument Representation and Coverage Analysis for Zero-Shot Long Document Summarization with Instruction Following LLMs
Mohamed Elaraby, Diane Litman
We introduce Argument Representation Coverage (ARC), a bottom-up evaluation framework that assesses how well summaries preserve salient arguments, a crucial issue in summarizing hi…
Persuasiveness of Generated Free-Text Rationales in Subjective Decisions: A Case Study on Pairwise Argument Ranking
Mohamed Elaraby, Diane Litman, Xiang Lorraine Li +1
Generating free-text rationales is among the emergent capabilities of Large Language Models (LLMs). These rationales have been found to enhance LLM performance across various NLP t…
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…
Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models
Mohamed Elaraby, Mengyin Lu, Jacob Dunn +6
Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP). Although convenient for research and practical applications, open-source LLMs with fewer paramet…
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…
ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining
Mohamed Elaraby, Diane Litman
A challenging task when generating summaries of legal documents is the ability to address their argumentative nature. We introduce a simple technique to capture the argumentative s…
Exploring Multitask Learning for Low-Resource AbstractiveSummarization
Ahmed Magooda, Mohamed Elaraby, Diane Litman
This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. In particular, we incorporate four different task…