activity
20172024
most citedMicrosoft Malware Classification Challenge

287 citations · 291 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 2 cited

InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers

Yakir Yehuda, Itzik Malkiel, Oren Barkan +3

Despite the many advances of Large Language Models (LLMs) and their unprecedented rapid evolution, their impact and integration into every facet of our daily lives is limited due t…

cs.CL2023★ 2 cited

GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models

Itzik Malkiel, Uri Alon, Yakir Yehuda +4

Transcriptions of phone calls are of significant value across diverse fields, such as sales, customer service, healthcare, and law enforcement. Nevertheless, the analysis of these…

cs.CL2022

An End-to-End Dialogue Summarization System for Sales Calls

Abedelkadir Asi, Song Wang, Roy Eisenstadt +4

Summarizing sales calls is a routine task performed manually by salespeople. We present a production system which combines generative models fine-tuned for customer-agent setting,…

cs.CR2018★ 287 cited

Microsoft Malware Classification Challenge

Royi Ronen, Marian Radu, Corina Feuerstein +2

The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0.5 terabytes, consisting of disassembly and bytecode of m…

cs.CR2017

Learning to Customize Network Security Rules

Michael Bargury, Roy Levin, Royi Ronen

Security is a major concern for organizations who wish to leverage cloud computing. In order to reduce security vulnerabilities, public cloud providers offer firewall functionaliti…