Ilanit Sobol & Emmy Abitbul

AI for Safer Relationships: Detecting Domestic Abuse Using Advanced NLP Methods
Ilanit Sobol
Emmy Abitbul


Ilanit Sobol and Emmy Abitbul, both alumni of the Technion’s Data Science and Engineering program, collaborated on this project as part of an Advanced NLP seminar, mentored by Roi Reichart. Emmy Abitbul has been working at Outbrain for over two years, starting as a Data Science Intern and now as a Data Scientist within the Marketplace Optimization Group. Meanwhile, Ilanit Sobol has worked in the healthcare sector, having experience as a Data Science Intern at GE HealthCare and XACT Robotics, developing and fine-tuning deep learning models to extract clinical data from medical reports. Ilanit is currently pursuing her Master’s in Data Science at the Technion, focusing on NLP applications in science, with a primary focus on suicide risk prediction.


Domestic violence is a widespread problem impacting millions globally. In the United States, one in four women experience serious partner violence in their lifetimes. Recognizing the importance of early detection in mitigating harm and providing support, this research leverages advancements in Natural Language Processing (NLP) and Large Language Models (LLMs) like GPT-4.

This study involves creating and annotating a high-quality dataset derived from the Reddit relationship advice forum. We applied annotation strategies based on the “Michal Sela” risk questionnaires and had multiple annotators annotate each example. Our study demonstrates the promising application of NLP models in identifying signs of domestic abuse, categorizing them into different risk levels, and interpreting the predictions using predefined confounders. The results, reveal the potential effectiveness of LLMs in detecting potentially abusive relationships, marking a significant step in utilizing AI for social welfare.


8:45 Reception
9:30 Opening remarks by WiDS TLV ambassadors Noah Eyal Altman, Or Basson, and Nitzan Gado
9:45 Dr. Aya Soffer, IBM: "Putting Generative AI to Work: What Have We Learned So Far?"
10:15 Prof. Reut Tsarfaty, Bar-llan University: "Will Hebrew Speakers Be Able to Use Generative AI in Their Native Tongue?"
10:45 Poster Pitches
10:55 Break
11:10 Lightning talks
12:30 Lunch & poster session
13:30 Roundtable session & poster session
14:15 Roundtable closing
14:30 Break
14:40 Naomi Ken Korem, Lightricks: "Mastering the Art of Generative Models: Training and Controlling Text-to-Video Models"
15:00 Dr. Yael Mathov, Intuit: "Surviving the AI-pocalypse: Your Guide to LLM Security"
15:20 Closing remarks
15:30 The end