14 citations · 23 across the 11 of their papers we have counts for
16 papers
Best Practices for Machine Learning Systems: An Industrial Framework for Analysis and Optimization
Georgios Christos Chouliaras, Kornel Kiełczewski, Amit Beka +2
In the last few years, the Machine Learning (ML) and Artificial Intelligence community has developed an increasing interest in Software Engineering (SE) for ML Systems leading to a…
Conversational Search with Mixed-Initiative -- Asking Good Clarification Questions backed-up by Passage Retrieval
Yosi Mass, Doron Cohen, Asaf Yehudai +1
We deal with the scenario of conversational search, where user queries are under-specified or ambiguous. This calls for a mixed-initiative setup. User-asks (queries) and system-ans…
TWEETSUMM -- A Dialog Summarization Dataset for Customer Service
Guy Feigenblat, Chulaka Gunasekara, Benjamin Sznajder +3
In a typical customer service chat scenario, customers contact a support center to ask for help or raise complaints, and human agents try to solve the issues. In most cases, at the…
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…
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…
Conversational Document Prediction to Assist Customer Care Agents
Jatin Ganhotra, Haggai Roitman, Doron Cohen +6
A frequent pattern in customer care conversations is the agents responding with appropriate webpage URLs that address users' needs. We study the task of predicting the documents th…
orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
Guy Lev, Michal Shmueli-Scheuer, Achiya Jerbi +1
Frequently Asked Questions (FAQ) webpages are created by organizations for their users. FAQs are used in several scenarios, e.g., to answer user questions. On the other hand, the c…
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…
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…
Controversy in Context
Benjamin Sznajder, Ariel Gera, Yonatan Bilu +5
With the growing interest in social applications of Natural Language Processing and Computational Argumentation, a natural question is how controversial a given concept is. Prior w…
A Study of BERT for Non-Factoid Question-Answering under Passage Length Constraints
Yosi Mass, Haggai Roitman, Shai Erera +3
We study the use of BERT for non-factoid question-answering, focusing on the passage re-ranking task under varying passage lengths. To this end, we explore the fine-tuning of BERT…
TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
Guy Lev, Michal Shmueli-Scheuer, Jonathan Herzig +2
Currently, no large-scale training data is available for the task of scientific paper summarization. In this paper, we propose a novel method that automatically generates summaries…
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…
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…
Learning Concept Abstractness Using Weak Supervision
Ella Rabinovich, Benjamin Sznajder, Artem Spector +4
We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data. Exploiting only minimal lingu…
Detecting Egregious Conversations between Customers and Virtual Agents
Tommy Sandbank, Michal Shmueli-Scheuer, Jonathan Herzig +3
Virtual agents are becoming a prominent channel of interaction in customer service. Not all customer interactions are smooth, however, and some can become almost comically bad. In…