| 2026 | AAAI | Extracting Interaction-Aware Monosemantic Concepts in Recommender Systems. | Dor Arviv, Yehonatan Elisha, Oren Barkan, Noam Koenigstein |
| 2026 | AAAI | Fidelity-Aware Recommendation Explanations via Stochastic Path Integration. | Oren Barkan, Yahlly Schein, Yehonatan Elisha, Veronika Bogina, Mikhail Baklanov, Noam Koenigstein |
| 2026 | AAAI | Rethinking Saliency Maps: A Cognitive Human Aligned Taxonomy and Evaluation Framework for Explanations. | Yehonatan Elisha, Seffi Cohen, Oren Barkan, Noam Koenigstein |
| 2025 | AAAI | BEE: Metric-Adapted Explanations via Baseline Exploration-Exploitation. | Oren Barkan, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein |
| 2025 | ICCV | Soft Local Completeness: Rethinking Completeness in XAI. | Ziv Weiss Haddad, Oren Barkan, Yehonatan Elisha, Noam Koenigstein |
| 2025 | SIGIR | Refining Fidelity Metrics for Explainable Recommendations. | Mikhail Baklanov, Veronika Bogina, Yehonatan Elisha, Yahlly Schein, Liron I. Allerhand, Oren Barkan, Noam Koenigstein |
| 2024 | ACL | InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers. | Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill, Royi Ronen, Noam Koenigstein |
| 2024 | CIKM | A Learning-based Approach for Explaining Language Models. | Oren Barkan, Yonatan Toib, Yehonatan Elisha, Noam Koenigstein |
| 2024 | CIKM | Probabilistic Path Integration with Mixture of Baseline Distributions. | Yehonatan Elisha, Oren Barkan, Noam Koenigstein |
| 2024 | EMNLP | Improving LLM Attributions with Randomized Path-Integration. | Oren Barkan, Yehonatan Elisha, Yonatan Toib, Jonathan Weill, Noam Koenigstein |
| 2024 | EMNLP | LLM Explainability via Attributive Masking Learning. | Oren Barkan, Yonatan Toib, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein |
| 2024 | ICASSP | SEGLLM: Topic-Oriented Call Segmentation Via LLM-Based Conversation Synthesis. | Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren, Oren Barkan, Royi Ronen, Noam Koenigstein |
| 2024 | ICASSP | Unsupervised Topic-Conditional Extractive Summarization. | Itzik Malkiel, Yakir Yehuda, Jonathan Ephrath, Ori Katz, Oren Barkan, Nir Nice, Noam Koenigstein |
| 2024 | WWW | A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems. | Oren Barkan, Veronika Bogina, Liya Gurevitch, Yuval Asher, Noam Koenigstein |
| 2023 | CIKM | Deep Integrated Explanations. | Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein |
| 2023 | CIKM | Harnessing GPT for Topic-Based Call Segmentation in Microsoft Dynamics 365 Sales. | Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren, Oren Barkan, Royi Ronen, Noam Koenigstein |
| 2023 | ICCV | Visual Explanations via Iterated Integrated Attributions. | Oren Barkan, Yehonatan Elisha, Yuval Asher, Amit Eshel, Noam Koenigstein |
| 2023 | ICCV | Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond. | Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein |
| 2023 | ICDM | Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. | Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein |
| 2023 | ICDM | Stochastic Integrated Explanations for Vision Models. | Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein |
| 2022 | ICASSP | Metricbert: Text Representation Learning Via Self-Supervised Triplet Training. | Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Yoni Weill, Noam Koenigstein |
| 2022 | RecSys | Learning to Ride a Buy-Cycle: A Hyper-Convolutional Model for Next Basket Repurchase Recommendation. | Ori Katz, Oren Barkan, Noam Koenigstein, Nir Zabari |
| 2022 | WWW | Interpreting BERT-based Text Similarity via Activation and Saliency Maps. | Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Jonathan Weill, Noam Koenigstein |
| 2021 | ACL | Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference. | Dvir Ginzburg, Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Koenigstein |
| 2021 | CIKM | GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps. | Oren Barkan, Omri Armstrong, Amir Hertz, Avi Caciularu, Ori Katz, Itzik Malkiel, Noam Koenigstein |
| 2021 | CIKM | Representation Learning via Variational Bayesian Networks. | Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz, Jonathan Weill, Itzik Malkiel, Noam Koenigstein |
| 2021 | CIKM | Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps. | Oren Barkan, Edan Hauon, Avi Caciularu, Ori Katz, Itzik Malkiel, Omri Armstrong, Noam Koenigstein |
| 2021 | CIKM | Anchor-based Collaborative Filtering. | Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Noam Koenigstein |
| 2021 | ICASSP | Cold Start Revisited: A Deep Hybrid Recommender with Cold-Warm Item Harmonization. | Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Yoni Weill, Noam Koenigstein |
| 2021 | ICDM | Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates. | Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, Noam Koenigstein |
| 2020 | AAAI | Scalable Attentive Sentence Pair Modeling via Distilled Sentence Embedding. | Oren Barkan, Noam Razin, Itzik Malkiel, Ori Katz, Avi Caciularu, Noam Koenigstein |
| 2020 | ACL | Bayesian Hierarchical Words Representation Learning. | Oren Barkan, Idan Rejwan, Avi Caciularu, Noam Koenigstein |
| 2020 | EMNLP | Optimizing BERT for Unlabeled Text-Based Items Similarity. | Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Razin, Ori Katz, Noam Koenigstein |
| 2020 | ICASSP | Attentive Item2vec: Neural Attentive User Representations. | Oren Barkan, Avi Caciularu, Ori Katz, Noam Koenigstein |
| 2020 | ICASSP | Neural Attentive Multiview Machines. | Oren Barkan, Ori Katz, Noam Koenigstein |
| 2020 | ICDM | Cold Item Recommendations via Hierarchical Item2vec. | Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz, Jonathan Weill, Itzik Malkiel, Noam Koenigstein |
| 2020 | RecSys | Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering. | Oren Barkan, Yonatan Fuchs, Avi Caciularu, Noam Koenigstein |
| 2019 | RecSys | CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations. | Oren Barkan, Noam Koenigstein, Eylon Yogev, Ori Katz |
| 2019 | RecSys | When actions speak louder than clicks: a combined model of purchase probability and long-term customer satisfaction. | Gal Lavee, Noam Koenigstein, Oren Barkan |
| 2019 | RecSys | Pick & merge: an efficient item filtering scheme for Windows store recommendations. | Adi Makmal, Jonathan Ephrath, Hilik Berezin, Liron I. Allerhand, Nir Nice, Noam Koenigstein |
| 2017 | AAAI | Low-Rank Factorization of Determinantal Point Processes. | Mike Gartrell, Ulrich Paquet, Noam Koenigstein |
| 2017 | RecSys | Rethinking Collaborative Filtering: A Practical Perspective on State-of-the-art Research Based on Real World Insights. | Noam Koenigstein |
| 2017 | WSDM | Groove Radio: A Bayesian Hierarchical Model for Personalized Playlist Generation. | Shay Ben-Elazar, Gal Lavee, Noam Koenigstein, Oren Barkan, Hilik Berezin, Ulrich Paquet, Tal Zaccai |
| 2016 | RecSys | Modelling Session Activity with Neural Embedding. | Oren Barkan, Yael Brumer, Noam Koenigstein |
| 2016 | RecSys | Item2vec: Neural Item Embedding for Collaborative Filtering. | Oren Barkan, Noam Koenigstein |
| 2016 | RecSys | Bayesian Low-Rank Determinantal Point Processes. | Mike Gartrell, Ulrich Paquet, Noam Koenigstein |
| 2016 | WWW | Beyond Collaborative Filtering: The List Recommendation Problem. | Oren Sar Shalom, Noam Koenigstein, Ulrich Paquet, Hastagiri P. Vanchinathan |
| 2014 | RecSys | Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. | Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, Ulrich Paquet |
| 2014 | RecSys | A Hybrid Explanations Framework for Collaborative Filtering Recommender Systems. | Shay Ben-Elazar, Noam Koenigstein |
| 2013 | RecSys | Towards scalable and accurate item-oriented recommendations. | Noam Koenigstein, Yehuda Koren |
| 2013 | RecSys | Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection. | Noam Koenigstein, Ulrich Paquet |
| 2013 | RecSys | Selecting content-based features for collaborative filtering recommenders. | Royi Ronen, Noam Koenigstein, Elad Ziklik, Nir Nice |
| 2013 | RecSys | Sage: recommender engine as a cloud service. | Royi Ronen, Noam Koenigstein, Elad Ziklik, Mikael Sitruk, Ronen Yaari, Neta Haiby-Weiss |
| 2013 | WWW | One-class collaborative filtering with random graphs. | Ulrich Paquet, Noam Koenigstein |
| 2012 | CIKM | Efficient retrieval of recommendations in a matrix factorization framework. | Noam Koenigstein, Parikshit Ram, Yuval Shavitt |
| 2012 | RecSys | The Xbox recommender system. | Noam Koenigstein, Nir Nice, Ulrich Paquet, Nir Schleyen |
| 2011 | RecSys | Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy. | Noam Koenigstein, Gideon Dror, Yehuda Koren |
| 2009 | ISM | Predicting Billboard Success Using Data-Mining in P2P Networks. | Noam Koenigstein, Yuval Shavitt, Noa Zilberman |
| 2008 | KDD | Spotting out emerging artists using geo-aware analysis of P2P query strings. | Noam Koenigstein, Yuval Shavitt, Tomer Tankel |