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20112021
most citedEven Better Framework for min-wise Based Algorithms

3 citations · 9 across the 3 of their papers we have counts for

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cs.CL20213 cited

HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles

Odellia Boni, Guy Feigenblat, Guy Lev +3

We present HowSumm, a novel large-scale dataset for the task of query-focused multi-document summarization (qMDS), which targets the use-case of generating actionable instructions…

cs.CL2021

Summary Grounded Conversation Generation

Chulaka Gunasekara, Guy Feigenblat, Benjamin Sznajder +2

Many conversation datasets have been constructed in the recent years using crowdsourcing. However, the data collection process can be time consuming and presents many challenges to…

cs.CL20203 cited

A Study of Human Summaries of Scientific Articles

Odellia Boni, Guy Feigenblat, Doron Cohen +2

Researchers and students face an explosion of newly published papers which may be relevant to their work. This led to a trend of sharing human summaries of scientific papers. We an…

cs.CL2019

A Summarization System for Scientific Documents

Shai Erera, Michal Shmueli-Scheuer, Guy Feigenblat +15

We present a novel system providing summaries for Computer Science publications. Through a qualitative user study, we identified the most valuable scenarios for discovery, explorat…

cs.CL2019

An Editorial Network for Enhanced Document Summarization

Edward Moroshko, Guy Feigenblat, Haggai Roitman +1

We suggest a new idea of Editorial Network - a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted se…

cs.CL2018

Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization

Haggai Roitman, Guy Feigenblat, David Konopnicki +2

We propose Dual-CES -- a novel unsupervised, query-focused, multi-document extractive summarizer. Dual-CES is designed to better handle the tradeoff between saliency and focus in s…