A Hybrid Approach for Automatic Model Recommendation. - Roman Vainshtein; Asnat Greenstein-Messica; Gilad Katz; Bracha Shapira; Lior Rokach (CIKM, 2018)

AutoGRD: Model Recommendation Through Graphical Dataset Representation. - Noy Cohen-Shapira; Lior Rokach; Bracha Shapira; Gilad Katz; Roman Vainshtein (CIKM, 2019)

Assessing the Quality of Scientific Papers. - Roman Vainshtein; Gilad Katz; Bracha Shapira; Lior Rokach (CoRR, 2019)

RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines. - Doron Laadan; Roman Vainshtein; Yarden Curiel; Gilad Katz; Lior Rokach (CoRR, 2019)

MetaTPOT: Enhancing A Tree-based Pipeline Optimization Tool Using Meta-Learning. - Doron Laadan; Roman Vainshtein; Yarden Curiel; Gilad Katz; Lior Rokach (CIKM, 2020)

DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering. - Yuval Heffetz; Roman Vainshtein; Gilad Katz; Lior Rokach (KDD, 2020)

Sequence Preserving Network Traffic Generation. - Sigal Shaked; Amos Zamir; Roman Vainshtein; Moshe Unger; Lior Rokach; Rami Puzis; Bracha Shapira (CoRR, 2020)

Automatic Machine Learning Derived from Scholarly Big Data. - Asnat Greenstein-Messica; Roman Vainshtein; Gilad Katz; Bracha Shapira; Lior Rokach (CoRR, 2020)

DeepCAN: Hybrid Method for Road Type Classification Using Vehicle Sensor Data for Smart Autonomous Mobility. - Adva Hadrian; Roman Vainshtein; Bracha Shapira; Lior Rokach (IEEE Trans. Intell. Transp. Syst., 2023)

ATLANTIS: A Framework for Automated Targeted Language-guided Augmentation Training for Robust Image Search. - Inderjeet Singh; Roman Vainshtein; Alon Zolfi; Asaf Shabtai; Tu Bui; Jonathan Brokman; Omer Hofman; Fumiyoshi Kasahara; Kentaro Tsuji; Hisashi Kojima (BMVC, 2024)

MONTRAGE: Monitoring Training for Attribution of Generative Diffusion Models. - Jonathan Brokman; Omer Hofman; Roman Vainshtein; Amit Giloni; Toshiya Shimizu; Inderjeet Singh; Oren Rachmil; Alon Zolfi; Asaf Shabtai; Yuki Unno; Hisashi Kojima (ECCV (75), 2024)

The Branch Not Taken: Predicting Branching in Online Conversations. - Shai Meital; Lior Rokach; Roman Vainshtein; Nir Grinberg (CoRR, 2024)

Automated algorithm selection using meta-learning and pre-trained deep convolution neural networks. - Itai Dagan; Roman Vainshtein; Gilad Katz; Lior Rokach (Inf. Fusion, 2024)

Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images. - Jonathan Brokman; Amit Giloni; Omer Hofman; Roman Vainshtein; Hisashi Kojima; Guy Gilboa (ICLR, 2025)

Insights and Current Gaps in Open-Source LLM Vulnerability Scanners: A Comparative Analysis. - Jonathan Brokman; Omer Hofman; Oren Rachmil; Inderjeet Singh; Vikas Pahuja; Rathina Sabapathy; Aishvariya Priya; Amit Giloni; Roman Vainshtein; Hisashi Kojima (RAIE, 2025)

Identifying Memorization of Diffusion Models Through p-Laplace Analysis. - Jonathan Brokman; Amit Giloni; Omer Hofman; Roman Vainshtein; Hisashi Kojima; Guy Gilboa (SSVM (1), 2025)

MAPS: A Multilingual Benchmark for Global Agent Performance and Security. - Omer Hofman; Oren Rachmil; Shamik Bose; Vikas Pahuja; Jonathan Brokman; Toshiya Shimizu; Trisha Starostina; Kelly Marchisio; Seraphina Goldfarb-Tarrant; Roman Vainshtein (CoRR, 2025)