| 2026 | AAAI | Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions. | Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron |
| 2026 | ACL | LR-DWM: Efficient Watermarking for Diffusion Language Models. | Ofek Raban, Gal Chechik, Ethan Fetaya |
| 2026 | WACV | Data-Driven Loss Functions for Inference-Time Optimization in Text-to-Image. | Sapir Esther Yiflach, Yuval Atzmon, Gal Chechik |
| 2025 | ACL | Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion. | Anum Afzal, Florian Matthes, Gal Chechik, Yftah Ziser |
| 2025 | CVPR | Make It Count: Text-to-Image Generation with an Accurate Number of Objects. | Lital Binyamin, Yoad Tewel, Hilit Segev, Eran Hirsch, Royi Rassin, Gal Chechik |
| 2025 | CVPR | TriTex: Learning Texture from a Single Mesh via Triplane Semantic Features. | Dana Cohen-Bar, Daniel Cohen-Or, Gal Chechik, Yoni Kasten |
| 2025 | CVPR | RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression. | Uri Gadot, Assaf Shocher, Shie Mannor, Gal Chechik, Assaf Hallak |
| 2025 | CVPR | Adapting to the Unknown: Training-Free Audio-Visual Event Perception with Dynamic Thresholds. | Eitan Shaar, Ariel Shaulov, Gal Chechik, Lior Wolf |
| 2025 | ICASSP | Classifier-Guided Captioning Across Modalities. | Ariel Shaulov, Tal Shaharabany, Eitan Shaar, Gal Chechik, Lior Wolf |
| 2025 | ICLR | Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. | Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari |
| 2025 | ICLR | Add-it: Training-Free Object Insertion in Images With Pretrained Diffusion Models. | Yoad Tewel, Rinon Gal, Dvir Samuel, Yuval Atzmon, Lior Wolf, Gal Chechik |
| 2025 | ICML | Policy Gradient with Tree Expansion. | Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik |
| 2025 | ICML | IT3: Idempotent Test-Time Training. | Nikita Durasov, Assaf Shocher, Doruk ner, Gal Chechik, Alexei A. Efros, Pascal Fua |
| 2025 | NAACL | Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I Models. | Michael Toker, Ido Galil, Hadas Orgad, Rinon Gal, Yoad Tewel, Gal Chechik, Yonatan Belinkov |
| 2025 | SiggraphA | OmnimatteZero: Fast Training-free Omnimatte with Pre-trained Video Diffusion Models. | Dvir Samuel, Matan Levy, Nir Darshan, Gal Chechik, Rami Ben-Ari |
| 2025 | SiggraphA | MaskedManipulator: Versatile Whole-Body Control for Loco-Manipulation. | Chen Tessler, Yifeng Jiang, Erwin Coumans, Zhengyi Luo, Xue Bin Peng, Gal Chechik |
| 2024 | AAAI | Generating Images of Rare Concepts Using Pre-trained Diffusion Models. | Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, Gal Chechik |
| 2024 | CVPR | Breathing Life Into Sketches Using Text-to-Video Priors. | Rinon Gal, Yael Vinker, Yuval Alaluf, Amit Bermano, Daniel Cohen-Or, Ariel Shamir, Gal Chechik |
| 2024 | ECCV | LCM-Lookahead for Encoder-Based Text-to-Image Personalization. | Rinon Gal, Or Lichter, Elad Richardson, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or |
| 2024 | ECCV | PlaMo: Plan and Move in Rich 3D Physical Environments. | Assaf Hallak, Gal Dalal, Chen Tessler, Kelly Guo, Shie Mannor, Gal Chechik |
| 2024 | EMNLP | Text2Model: Text-based Model Induction for Zero-shot Image Classification. | Ohad Amosy, Tomer Volk, Eilam Shapira, Eyal Ben-David, Roi Reichart, Gal Chechik |
| 2024 | ICML | Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning. | Idan Achituve, Idit Diamant, Arnon Netzer, Gal Chechik, Ethan Fetaya |
| 2024 | ICML | Equivariant Deep Weight Space Alignment. | Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron |
| 2024 | ICML | Improved Generalization of Weight Space Networks via Augmentations. | Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron |
| 2024 | WACV | Late to the party? On-demand unlabeled personalized federated learning. | Ohad Amosy, Gal Eyal, Gal Chechik |
| 2024 | SiggraphA | DiffUHaul: A Training-Free Method for Object Dragging in Images. | Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie |
| 2023 | AAAI | Planning and Learning with Adaptive Lookahead. | Aviv Rosenberg, Assaf Hallak, Shie Mannor, Gal Chechik, Gal Dalal |
| 2023 | BMVC | DisCLIP: Open-Vocabulary Referring Expression Generation. | Lior Bracha, Eitan Shaar, Aviv Shamsian, Ethan Fetaya, Gal Chechik |
| 2023 | CCGRID | Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs. | Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal |
| 2023 | EMNLP | Example-based Hypernetworks for Multi-source Adaptation to Unseen Domains. | Tomer Volk, Eyal Ben-David, Ohad Amosy, Gal Chechik, Roi Reichart |
| 2023 | ICLR | An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. | Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit Haim Bermano, Gal Chechik, Daniel Cohen-Or |
| 2023 | ICLR | Personalized Federated Learning for Medical Segmentation using Hypernetworks. | Hilit Segev, Gal Chechik |
| 2023 | ICML | Learning to Initiate and Reason in Event-Driven Cascading Processes. | Yuval Atzmon, Eli A. Meirom, Shie Mannor, Gal Chechik |
| 2023 | ICML | Graph Positional Encoding via Random Feature Propagation. | Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron |
| 2023 | ICML | Equivariant Architectures for Learning in Deep Weight Spaces. | Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron |
| 2023 | ICML | Auxiliary Learning as an Asymmetric Bargaining Game. | Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya |
| 2023 | SIGGRAPH | CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. | Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng |
| 2023 | SIGGRAPH | Key-Locked Rank One Editing for Text-to-Image Personalization. | Yoad Tewel, Rinon Gal, Gal Chechik, Yuval Atzmon |
| 2023 | UAI | Guided Deep Kernel Learning. | Idan Achituve, Gal Chechik, Ethan Fetaya |
| 2023 | SiggraphA | Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models. | Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, Amit H. Bermano |
| 2022 | AAAI | Reinforcement Learning for Datacenter Congestion Control. | Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor |
| 2022 | CVPR | DETReg: Unsupervised Pretraining with Region Priors for Object Detection. | Amir Bar, Xin Wang, Vadim Kantorov, Colorado J. Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson |
| 2022 | CVPR | Object-Region Video Transformers. | Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson |
| 2022 | ECCV | "This Is My Unicorn, Fluffy": Personalizing Frozen Vision-Language Representations. | Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, Yuval Atzmon |
| 2022 | ICLR | On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. | Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit |
| 2022 | ICML | Optimizing Tensor Network Contraction Using Reinforcement Learning. | Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik |
| 2022 | ICML | Multi-Task Learning as a Bargaining Game. | Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya |
| 2022 | WACV | Coupled Training for Multi-Source Domain Adaptation. | Ohad Amosy, Gal Chechik |
| 2021 | ICCV | ACAV100M: Automatic Curation of Large-Scale Datasets for Audio-Visual Video Representation Learning. | Sangho Lee, Jiwan Chung, Youngjae Yu, Gunhee Kim, Thomas M. Breuel, Gal Chechik, Yale Song |
| 2021 | ICCV | Distributional Robustness Loss for Long-tail Learning. | Dvir Samuel, Gal Chechik |
| 2021 | ICLR | Auxiliary Learning by Implicit Differentiation. | Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya |
| 2021 | ICLR | Learning the Pareto Front with Hypernetworks. | Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik |
| 2021 | ICML | GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning. | Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya |
| 2021 | ICML | Compositional Video Synthesis with Action Graphs. | Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson |
| 2021 | ICML | Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. | Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik |
| 2021 | ICML | Personalized Federated Learning using Hypernetworks. | Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik |
| 2021 | ICML | From Local Structures to Size Generalization in Graph Neural Networks. | Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron |
| 2021 | IJCAI | On Learning Sets of Symmetric Elements (Extended Abstract). | Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya |
| 2021 | WACV | Self-Supervised Learning for Domain Adaptation on Point Clouds. | Idan Achituve, Haggai Maron, Gal Chechik |
| 2021 | WACV | From generalized zero-shot learning to long-tail with class descriptors. | Dvir Samuel, Yuval Atzmon, Gal Chechik |
| 2021 | UAI | Known unknowns: Learning novel concepts using reasoning-by-elimination. | Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, Gal Chechik |
| 2020 | ECCV | Contrastive Learning for Weakly Supervised Phrase Grounding. | Tanmay Gupta, Arash Vahdat, Gal Chechik, Xiaodong Yang, Jan Kautz, Derek Hoiem |
| 2020 | ECCV | Learning Canonical Representations for Scene Graph to Image Generation. | Roei Herzig, Amir Bar, Huijuan Xu, Gal Chechik, Trevor Darrell, Amir Globerson |
| 2020 | ECCV | Learning Object Permanence from Video. | Aviv Shamsian, Ofri Kleinfeld, Amir Globerson, Gal Chechik |
| 2020 | EMNLP | ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization. | Tzuf Paz-Argaman, Reut Tsarfaty, Gal Chechik, Yuval Atzmon |
| 2020 | ICML | On Learning Sets of Symmetric Elements. | Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya |
| 2020 | WACV | Differentiable Scene Graphs. | Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson |
| 2019 | CVPR | Adaptive Confidence Smoothing for Generalized Zero-Shot Learning. | Yuval Atzmon, Gal Chechik |
| 2019 | CVPR | Informative Object Annotations: Tell Me Something I Don't Know. | Lior Bracha, Gal Chechik |
| 2019 | EMNLP | Multilingual word translation using auxiliary languages. | Hagai Taitelbaum, Gal Chechik, Jacob Goldberger |
| 2019 | EMNLP | A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation. | Hagai Taitelbaum, Gal Chechik, Jacob Goldberger |
| 2019 | ICASSP | Network Adaptation Strategies for Learning New Classes without Forgetting the Original Ones. | Hagai Taitelbaum, Gal Chechik, Jacob Goldberger |
| 2019 | ICCV | Joint Optimization for Cooperative Image Captioning. | Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik |
| 2018 | UAI | Probabilistic AND-OR Attribute Grouping for Zero-Shot Learning. | Yuval Atzmon, Gal Chechik |
| 2017 | CVPR | Context-Aware Captions from Context-Agnostic Supervision. | Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik |
| 2017 | CVPR | Learning from Noisy Large-Scale Datasets with Minimal Supervision. | Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie |
| 2017 | ICANN | DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders. | Ido Cohen, Eli (Omid) David, Nathan S. Netanyahu, Noa Liscovitch, Gal Chechik |
| 2017 | IJCAI | Instance-Level Label Propagation with Multi-Instance Learning. | Qifan Wang, Gal Chechik, Chen Sun, Bin Shen |
| 2015 | KDD | Probabilistic Graphical Models of Dyslexia. | Yair Lakretz, Gal Chechik, Naama Friedmann, Michal Rosen-Zvi |
| 2014 | ICML | Coordinate-descent for learning orthogonal matrices through Givens rotations. | Uri Shalit, Gal Chechik |
| 2013 | ICML | Modeling Musical Influence with Topic Models. | Uri Shalit, Daphna Weinshall, Gal Chechik |
| 2012 | ICML | Adaptive Regularization for Similarity Measures. | Koby Crammer, Gal Chechik |
| 2011 | ICASSP | Sparse coding of auditory features for machine hearing in interference. | Richard F. Lyon, Jay Ponte, Gal Chechik |
| 2010 | CVPR | Object separation in x-ray image sets. | Geremy Heitz, Gal Chechik |
| 2009 | IBPRIA | Large Scale Online Learning of Image Similarity through Ranking. | Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio |
| 2006 | AAAI | Embedding Heterogeneous Data Using Statistical Models. | Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby |
| 2004 | ICML | A needle in a haystack: local one-class optimization. | Koby Crammer, Gal Chechik |
| 2003 | UAI | Sufficient Dimensionality Reduction with Irrelevance Statistics. | Amir Globerson, Gal Chechik, Naftali Tishby |