Spotting out emerging artists using geo-aware analysis of P2P query strings. - Noam Koenigstein; Yuval Shavitt; Tomer Tankel (KDD, 2008)

Predicting Billboard Success Using Data-Mining in P2P Networks. - Noam Koenigstein; Yuval Shavitt; Noa Zilberman (ISM, 2009)

Song Ranking based on Piracy in Peer-to-Peer Networks. - Noam Koenigstein; Yuval Shavitt (ISMIR, 2009)

A framework for extracting musical similarities from peer-to-peer networks. - Noam Koenigstein; Yuval Shavitt; Tomer Tankel; Ela Weinsberg; Udi Weinsberg (ICME, 2010)

Collaborative Filtering Based on P2P Networks. - Noam Koenigstein; Gert R. G. Lanckriet; Brian McFee; Yuval Shavitt (ISMIR, 2010)

On the Applicability of Peer-to-peer Data in Music Information Retrieval Research. - Noam Koenigstein; Yuval Shavitt; Ela Weinsberg; Udi Weinsberg (ISMIR, 2010)

What's Hot? Estimating Country-specific Artist Popularity. - Markus Schedl; Tim Pohle; Noam Koenigstein; Peter Knees (ISMIR, 2010)

Analyzing the DC File Sharing Network. - Pavel Gurvich; Noam Koenigstein; Yuval Shavitt (Peer-to-Peer Computing, 2010)

Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy. - Noam Koenigstein; Gideon Dror; Yehuda Koren (RecSys, 2011)

Efficient retrieval of recommendations in a matrix factorization framework. - Noam Koenigstein; Parikshit Ram; Yuval Shavitt (CIKM, 2012)

The Xbox recommender system. - Noam Koenigstein; Nir Nice; Ulrich Paquet; Nir Schleyen (RecSys, 2012)

Talent scouting in P2P networks. - Noam Koenigstein; Yuval Shavitt (Comput. Networks, 2012)

Measuring the validity of peer-to-peer data for information retrieval applications. - Noam Koenigstein; Yuval Shavitt; Ela Weinsberg; Udi Weinsberg (Comput. Networks, 2012)

The Yahoo! Music Dataset and KDD-Cup '11. - Gideon Dror; Noam Koenigstein; Yehuda Koren; Markus Weimer (KDD Cup, 2012)

Web-Scale Media Recommendation Systems. - Gideon Dror; Noam Koenigstein; Yehuda Koren (Proc. IEEE, 2012)

Towards scalable and accurate item-oriented recommendations. - Noam Koenigstein; Yehuda Koren (RecSys, 2013)

Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection. - Noam Koenigstein; Ulrich Paquet (RecSys, 2013)

Selecting content-based features for collaborative filtering recommenders. - Royi Ronen; Noam Koenigstein; Elad Ziklik; Nir Nice (RecSys, 2013)

Sage: recommender engine as a cloud service. - Royi Ronen; Noam Koenigstein; Elad Ziklik; Mikael Sitruk; Ronen Yaari; Neta Haiby-Weiss (RecSys, 2013)

One-class collaborative filtering with random graphs. - Ulrich Paquet; Noam Koenigstein (WWW, 2013)

One-class Collaborative Filtering with Random Graphs: Annotated Version. - Ulrich Paquet; Noam Koenigstein (CoRR, 2013)

Mining User Generated Data for Music Information Retrieval. - Markus Schedl; Mohamed Sordo; Noam Koenigstein; Udi Weinsberg (Mining User Generated Content, 2014)

Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. - Yoram Bachrach; Yehuda Finkelstein; Ran Gilad-Bachrach; Liran Katzir 001; Noam Koenigstein; Nir Nice; Ulrich Paquet (RecSys, 2014)

A Hybrid Explanations Framework for Collaborative Filtering Recommender Systems. - Shay Ben-Elazar; Noam Koenigstein (RecSys Posters, 2014)

A large-scale exploration of group viewing patterns. - Allison June-Barlow Chaney; Mike Gartrell; Jake M. Hofman; John Guiver; Noam Koenigstein; Pushmeet Kohli; Ulrich Paquet (TVX, 2014)

ITEM2VEC: Neural item embedding for collaborative filtering. - Oren Barkan; Noam Koenigstein (MLSP, 2016)

Modelling Session Activity with Neural Embedding. - Oren Barkan; Yael Brumer; Noam Koenigstein (RecSys Posters, 2016)

Bayesian Low-Rank Determinantal Point Processes. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (RecSys, 2016)

Beyond Collaborative Filtering: The List Recommendation Problem. - Oren Sar Shalom; Noam Koenigstein; Ulrich Paquet; Hastagiri P. Vanchinathan (WWW, 2016)

The Deep Journey from Content to Collaborative Filtering. - Oren Barkan; Noam Koenigstein; Eylon Yogev (CoRR, 2016)

Low-Rank Factorization of Determinantal Point Processes for Recommendation. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (CoRR, 2016)

The Bayesian Low-Rank Determinantal Point Process Mixture Model. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (CoRR, 2016)

Low-Rank Factorization of Determinantal Point Processes. - Mike Gartrell; Ulrich Paquet; Noam Koenigstein (AAAI, 2017)

Rethinking Collaborative Filtering: A Practical Perspective on State-of-the-art Research Based on Real World Insights. - Noam Koenigstein (RecSys, 2017)

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 (WSDM, 2017)

CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations. - Oren Barkan; Noam Koenigstein; Eylon Yogev; Ori Katz (RecSys, 2019)

When actions speak louder than clicks: a combined model of purchase probability and long-term customer satisfaction. - Gal Lavee; Noam Koenigstein; Oren Barkan (RecSys, 2019)

Pick & merge: an efficient item filtering scheme for Windows store recommendations. - Adi Makmal; Jonathan Ephrath; Hilik Berezin; Liron I. Allerhand; Nir Nice; Noam Koenigstein (RecSys, 2019)

InverSynth: Deep Estimation of Synthesizer Parameter Configurations From Audio Signals. - Oren Barkan; David Tsiris; Ori Katz; Noam Koenigstein (IEEE ACM Trans. Audio Speech Lang. Process., 2019)

Scalable Attentive Sentence Pair Modeling via Distilled Sentence Embedding. - Oren Barkan; Noam Razin; Itzik Malkiel; Ori Katz; Avi Caciularu; Noam Koenigstein (AAAI, 2020)

Bayesian Hierarchical Words Representation Learning. - Oren Barkan; Idan Rejwan; Avi Caciularu; Noam Koenigstein (ACL, 2020)

Optimizing BERT for Unlabeled Text-Based Items Similarity. - Itzik Malkiel; Oren Barkan; Avi Caciularu; Noam Razin; Ori Katz; Noam Koenigstein (EMNLP (Findings), 2020)

Attentive Item2vec: Neural Attentive User Representations. - Oren Barkan; Avi Caciularu; Ori Katz; Noam Koenigstein (ICASSP, 2020)

Neural Attentive Multiview Machines. - Oren Barkan; Ori Katz; Noam Koenigstein (ICASSP, 2020)

Cold Item Recommendations via Hierarchical Item2vec. - Oren Barkan; Avi Caciularu; Idan Rejwan; Ori Katz; Jonathan Weill; Itzik Malkiel; Noam Koenigstein (ICDM, 2020)

Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering. - Oren Barkan; Yonatan Fuchs; Avi Caciularu; Noam Koenigstein (RecSys, 2020)

Autoencoders. - Dor Bank; Noam Koenigstein; Raja Giryes (CoRR, 2020)

RecoBERT: A Catalog Language Model for Text-Based Recommendations. - Itzik Malkiel; Oren Barkan; Avi Caciularu; Noam Razin; Ori Katz; Noam Koenigstein (CoRR, 2020)

Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference. - Dvir Ginzburg; Itzik Malkiel; Oren Barkan; Avi Caciularu; Noam Koenigstein (ACL/IJCNLP (Findings), 2021)

GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps. - Oren Barkan; Omri Armstrong; Amir Hertz; Avi Caciularu; Ori Katz; Itzik Malkiel; Noam Koenigstein (CIKM, 2021)

Representation Learning via Variational Bayesian Networks. - Oren Barkan; Avi Caciularu; Idan Rejwan; Ori Katz; Jonathan Weill; Itzik Malkiel; Noam Koenigstein (CIKM, 2021)

Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps. - Oren Barkan; Edan Hauon; Avi Caciularu; Ori Katz; Itzik Malkiel; Omri Armstrong; Noam Koenigstein (CIKM, 2021)

Anchor-based Collaborative Filtering. - Oren Barkan; Roy Hirsch; Ori Katz; Avi Caciularu; Noam Koenigstein (CIKM, 2021)

Cold Start Revisited: A Deep Hybrid Recommender with Cold-Warm Item Harmonization. - Oren Barkan; Roy Hirsch; Ori Katz; Avi Caciularu; Yoni Weill; Noam Koenigstein (ICASSP, 2021)

Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates. - Oren Barkan; Roy Hirsch; Ori Katz; Avi Caciularu; Jonathan Weill; Noam Koenigstein (ICDM, 2021)

Metricbert: Text Representation Learning Via Self-Supervised Triplet Training. - Itzik Malkiel; Dvir Ginzburg; Oren Barkan; Avi Caciularu; Yoni Weill; Noam Koenigstein (ICASSP, 2022)

Learning to Ride a Buy-Cycle: A Hyper-Convolutional Model for Next Basket Repurchase Recommendation. - Ori Katz; Oren Barkan; Noam Koenigstein; Nir Zabari (RecSys, 2022)

Interpreting BERT-based Text Similarity via Activation and Saliency Maps. - Itzik Malkiel; Dvir Ginzburg; Oren Barkan; Avi Caciularu; Jonathan Weill; Noam Koenigstein (WWW, 2022)

Deep Integrated Explanations. - Oren Barkan; Yehonatan Elisha; Jonathan Weill; Yuval Asher; Amit Eshel; Noam Koenigstein (CIKM, 2023)

Harnessing GPT for Topic-Based Call Segmentation in Microsoft Dynamics 365 Sales. - Itzik Malkiel; Uri Alon 002; Yakir Yehuda; Shahar Keren; Oren Barkan; Royi Ronen; Noam Koenigstein (CIKM, 2023)

Visual Explanations via Iterated Integrated Attributions. - Oren Barkan; Yehonatan Elisha; Yuval Asher; Amit Eshel; Noam Koenigstein (ICCV, 2023)

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 (ICCV, 2023)

Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. - Oren Barkan; Yuval Asher; Amit Eshel; Yehonatan Elisha; Noam Koenigstein (ICDM, 2023)

Stochastic Integrated Explanations for Vision Models. - Oren Barkan; Yehonatan Elisha; Jonathan Weill; Yuval Asher; Amit Eshel; Noam Koenigstein (ICDM, 2023)

Inversynth II: Sound Matching via Self-Supervised Synthesizer-Proxy and Inference-Time Finetuning. - Oren Barkan; Shlomi Shvartzman; Noy Uzrad; Moshe Laufer; Almog Elharar; Noam Koenigstein (ISMIR, 2023)

Not All Memories Created Equal: Dynamic User Representations for Collaborative Filtering. - Keren Gaiger; Oren Barkan; Shir Tsipory-Samuel; Noam Koenigstein (IEEE Access, 2023)

Detecting Security Patches via Behavioral Data in Code Repositories. - Nitzan Farhi; Noam Koenigstein; Yuval Shavitt (CoRR, 2023)

GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models. - Itzik Malkiel; Uri Alon 002; Yakir Yehuda; Shahar Keren; Oren Barkan; Royi Ronen; Noam Koenigstein (CoRR, 2023)

InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers. - Yakir Yehuda; Itzik Malkiel; Oren Barkan; Jonathan Weill; Royi Ronen; Noam Koenigstein (ACL (1), 2024)

A Learning-based Approach for Explaining Language Models. - Oren Barkan; Yonatan Toib; Yehonatan Elisha; Noam Koenigstein (CIKM, 2024)

Probabilistic Path Integration with Mixture of Baseline Distributions. - Yehonatan Elisha; Oren Barkan; Noam Koenigstein (CIKM, 2024)

Improving LLM Attributions with Randomized Path-Integration. - Oren Barkan; Yehonatan Elisha; Yonatan Toib; Jonathan Weill; Noam Koenigstein (EMNLP (Findings), 2024)

LLM Explainability via Attributive Masking Learning. - Oren Barkan; Yonatan Toib; Yehonatan Elisha; Jonathan Weill; Noam Koenigstein (EMNLP (Findings), 2024)

SEGLLM: Topic-Oriented Call Segmentation Via LLM-Based Conversation Synthesis. - Itzik Malkiel; Uri Alon 002; Yakir Yehuda; Shahar Keren; Oren Barkan; Royi Ronen; Noam Koenigstein (ICASSP, 2024)

Unsupervised Topic-Conditional Extractive Summarization. - Itzik Malkiel; Yakir Yehuda; Jonathan Ephrath; Ori Katz; Oren Barkan; Nir Nice; Noam Koenigstein (ICASSP, 2024)

A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems. - Oren Barkan; Veronika Bogina; Liya Gurevitch; Yuval Asher; Noam Koenigstein (WWW, 2024)

DiffMoog: a Differentiable Modular Synthesizer for Sound Matching. - Noy Uzrad; Oren Barkan; Almog Elharar; Shlomi Shvartzman; Moshe Laufer; Lior Wolf; Noam Koenigstein (CoRR, 2024)

In Search of Truth: An Interrogation Approach to Hallucination Detection. - Yakir Yehuda; Itzik Malkiel; Oren Barkan; Jonathan Weill; Royi Ronen; Noam Koenigstein (CoRR, 2024)

Modeling users' heterogeneous taste with diversified attentive user profiles. - Oren Barkan; Tom Shaked; Yonatan Fuchs; Noam Koenigstein (User Model. User Adapt. Interact., 2024)

BEE: Metric-Adapted Explanations via Baseline Exploration-Exploitation. - Oren Barkan; Yehonatan Elisha; Jonathan Weill; Noam Koenigstein (AAAI, 2025)

Refining Fidelity Metrics for Explainable Recommendations. - Mikhail Baklanov; Veronika Bogina; Yehonatan Elisha; Yahlly Schein; Liron I. Allerhand; Oren Barkan; Noam Koenigstein (SIGIR, 2025)

Unveiling Creativity in Student Code: A Gaussian Mixture Model Approach. - Veronika Bogina; Arnon Hershkovitz; Noam Koenigstein (UMAP, 2025)

PatchView: Multi-modality detection of security patches. - Nitzan Farhi; Noam Koenigstein; Yuval Shavitt (Comput. Secur., 2025)

Personalized Cadence Awareness for Next Basket Recommendation. - Ori Katz; Oren Barkan; Noam Koenigstein (Trans. Recomm. Syst., 2025)

KPAR: Knowledge-aware Path-based Attentive Recommender with Interpretability. - Leigh Eytan; Veronika Bogina; Irad Ben-Gal; Noam Koenigstein (Trans. Recomm. Syst., 2025)