Amir Globerson
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
94
Venues
16
Active years
2002–2026
Best venue rank
A*
Where they publish
Papers
94 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. | Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier |
| 2025 | AAAI | Teaching Models to Improve on Tape. | Liat Bezalel, Eyal Orgad, Amir Globerson |
| 2025 | ICLR | DeciMamba: Exploring the Length Extrapolation Potential of Mamba. | Assaf Ben-Kish, Itamar Zimerman, Shady Abu-Hussein, Nadav Cohen, Amir Globerson, Lior Wolf, Raja Giryes |
| 2025 | ICLR | Do LLMs have Consistent Values? | Naama Rozen, Liat Bezalel, Gal Elidan, Amir Globerson, Ella Daniel |
| 2024 | AAAI | TREE-G: Decision Trees Contesting Graph Neural Networks. | Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach |
| 2024 | ECCV | EgoPet: Egomotion and Interaction Data from an Animal's Perspective. | Amir Bar, Arya Bakhtiar, Danny Tran, Antonio Loquercio, Jathushan Rajasegaran, Yann LeCun, Amir Globerson, Trevor Darrell |
| 2024 | ECCV | Finding Visual Task Vectors. | Alberto Hojel, Yutong Bai, Trevor Darrell, Amir Globerson, Amir Bar |
| 2024 | EMNLP | Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries. | Eden Biran, Daniela Gottesman, Sohee Yang, Mor Geva, Amir Globerson |
| 2024 | ICML | Stochastic positional embeddings improve masked image modeling. | Amir Bar, Florian Bordes, Assaf Shocher, Mido Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun |
| 2024 | ICML | Graph Neural Networks Use Graphs When They Shouldn't. | Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach, Amir Globerson |
| 2024 | ICML | Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States. | Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen |
| 2024 | WACV | PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data. | Roei Herzig, Ofir Abramovich, Elad Ben-Avraham, Assaf Arbelle, Leonid Karlinsky, Ariel Shamir, Trevor Darrell, Amir Globerson |
| 2023 | ACL | Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment. | Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson |
| 2023 | ACL | What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary. | Ori Ram, Liat Bezalel, Adi Zicher, Yonatan Belinkov, Jonathan Berant, Amir Globerson |
| 2023 | EACL | Crawling The Internal Knowledge-Base of Language Models. | Roi Cohen, Mor Geva, Jonathan Berant, Amir Globerson |
| 2023 | EMNLP | LM vs LM: Detecting Factual Errors via Cross Examination. | Roi Cohen, May Hamri, Mor Geva, Amir Globerson |
| 2023 | EMNLP | Dissecting Recall of Factual Associations in Auto-Regressive Language Models. | Mor Geva, Jasmijn Bastings, Katja Filippova, Amir Globerson |
| 2023 | EMNLP | In-Context Learning Creates Task Vectors. | Roee Hendel, Mor Geva, Amir Globerson |
| 2023 | EMNLP | Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs. | Roei Herzig, Alon Mendelson, Leonid Karlinsky, Assaf Arbelle, Rogrio Feris, Trevor Darrell, Amir Globerson |
| 2023 | ICLR | Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets. | Edo Cohen-Karlik, Itamar Menuhin-Gruman, Raja Giryes, Nadav Cohen, Amir Globerson |
| 2022 | AISTATS | On the Implicit Bias of Gradient Descent for Temporal Extrapolation. | Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson |
| 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 | EMNLP | Text-Only Training for Image Captioning using Noise-Injected CLIP. | David Nukrai, Ron Mokady, Amir Globerson |
| 2022 | ICML | Efficient Learning of CNNs using Patch Based Features. | Alon Brutzkus, Amir Globerson, Eran Malach, Alon Regev Netser, Shai Shalev-Shwartz |
| 2022 | NAACL | Learning to Retrieve Passages without Supervision. | Ori Ram, Gal Shachaf, Omer Levy, Jonathan Berant, Amir Globerson |
| 2022 | UAI | On the inductive bias of neural networks for learning read-once DNFs. | Ido Bronstein, Alon Brutzkus, Amir Globerson |
| 2022 | UAI | Active learning with label comparisons. | Gal Yona, Shay Moran, Gal Elidan, Amir Globerson |
| 2021 | ACL | Few-Shot Question Answering by Pretraining Span Selection. | Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy |
| 2021 | EACL | BERTese: Learning to Speak to BERT. | Adi Haviv, Jonathan Berant, Amir Globerson |
| 2021 | ICCV | Explaining in Style: Training a GAN to explain a classifier in StyleSpace. | Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri |
| 2021 | ICML | On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent. | Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry |
| 2021 | ICML | Compositional Video Synthesis with Action Graphs. | Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson |
| 2021 | ICML | Towards Understanding Learning in Neural Networks with Linear Teachers. | Roei Sarussi, Alon Brutzkus, Amir Globerson |
| 2021 | UAI | An optimization and generalization analysis for max-pooling networks. | Alon Brutzkus, Amir Globerson |
| 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 | A Simple and Effective Model for Answering Multi-span Questions. | Elad Segal, Avia Efrat, Mor Shoham, Amir Globerson, Jonathan Berant |
| 2020 | EMNLP | Pre-training Mention Representations in Coreference Models. | Yuval Varkel, Amir Globerson |
| 2020 | ICLR | Optimal Strategies Against Generative Attacks. | Roy Mor, Erez Peterfreund, Matan Gavish, Amir Globerson |
| 2020 | WACV | Differentiable Scene Graphs. | Moshiko Raboh, Roei Herzig, Jonathan Berant, Gal Chechik, Amir Globerson |
| 2019 | ACL | Coreference Resolution with Entity Equalization. | Ben Kantor, Amir Globerson |
| 2019 | AISTATS | Learning Rules-First Classifiers. | Deborah Cohen, Amit Daniely, Amir Globerson, Gal Elidan |
| 2019 | ICDE | Explaining Queries Over Web Tables to Non-experts. | Jonathan Berant, Daniel Deutch, Amir Globerson, Tova Milo, Tomer Wolfson |
| 2019 | ICML | Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem. | Alon Brutzkus, Amir Globerson |
| 2019 | NAACL | Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing. | Tal Schuster, Ori Ram, Regina Barzilay, Amir Globerson |
| 2018 | ACL | Weakly Supervised Semantic Parsing with Abstract Examples. | Omer Goldman, Veronica Latcinnik, Ehud Nave, Amir Globerson, Jonathan Berant |
| 2018 | AISTATS | Semi-Supervised Learning with Competitive Infection Models. | Nir Rosenfeld, Amir Globerson |
| 2018 | ICLR | SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data. | Alon Brutzkus, Amir Globerson, Eran Malach, Shai Shalev-Shwartz |
| 2018 | ICML | Predict and Constrain: Modeling Cardinality in Deep Structured Prediction. | Nataly Brukhim, Amir Globerson |
| 2018 | ICML | Learning to Optimize Combinatorial Functions. | Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer |
| 2017 | COLT | Effective Semisupervised Learning on Manifolds. | Amir Globerson, Roi Livni, Shai Shalev-Shwartz |
| 2017 | ICML | Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs. | Alon Brutzkus, Amir Globerson |
| 2017 | ICML | Learning Infinite Layer Networks Without the Kernel Trick. | Roi Livni, Daniel Carmon, Amir Globerson |
| 2017 | UAI | Learning and Inference with Expectations. | Amir Globerson |
| 2016 | ACL | Collective Entity Resolution with Multi-Focal Attention. | Amir Globerson, Nevena Lazic, Soumen Chakrabarti, Amarnag Subramanya, Michael Ringgaard, Fernando Pereira |
| 2016 | AISTATS | Improper Deep Kernels. | Uri Heinemann, Roi Livni, Elad Eban, Gal Elidan, Amir Globerson |
| 2016 | WSDM | Discriminative Learning of Infection Models. | Nir Rosenfeld, Mor Nitzan, Amir Globerson |
| 2015 | ICML | How Hard is Inference for Structured Prediction? | Amir Globerson, Tim Roughgarden, David A. Sontag, Cafer Yildirim |
| 2015 | NAACL | Template Kernels for Dependency Parsing. | Hillel Taub-Tabib, Yoav Goldberg, Amir Globerson |
| 2014 | ACL | Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees. | Yuan Zhang, Tao Lei, Regina Barzilay, Tommi S. Jaakkola, Amir Globerson |
| 2014 | AISTATS | Efficient Lifting of MAP LP Relaxations Using k-Locality. | Martin Mladenov, Kristian Kersting, Amir Globerson |
| 2014 | AISTATS | Learning Structured Models with the AUC Loss and Its Generalizations. | Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson |
| 2014 | ICML | Discrete Chebyshev Classifiers. | Elad Eban, Elad Mezuman, Amir Globerson |
| 2014 | ICML | Inferning with High Girth Graphical Models. | Uri Heinemann, Amir Globerson |
| 2014 | ICML | Spectral Regularization for Max-Margin Sequence Tagging. | Ariadna Quattoni, Borja Balle, Xavier Carreras, Amir Globerson |
| 2014 | UAI | Lifted Message Passing as Reparametrization of Graphical Models. | Martin Mladenov, Amir Globerson, Kristian Kersting |
| 2014 | UAI | Tightness Results for Local Consistency Relaxations in Continuous MRFs. | Yoav Wald, Amir Globerson |
| 2013 | ACL | Transfer Learning for Constituency-Based Grammars. | Yuan Zhang, Regina Barzilay, Amir Globerson |
| 2013 | ICCV | Higher Order Matching for Consistent Multiple Target Tracking. | Chetan Arora, Amir Globerson |
| 2013 | ICML | Vanishing Component Analysis. | Roi Livni, David Lehavi, Sagi Schein, Hila Nachlieli, Shai Shalev-Shwartz, Amir Globerson |
| 2013 | ICML | The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification. | Ofir Pele, Ben Taskar, Amir Globerson, Michael Werman |
| 2013 | UAI | Learning Max-Margin Tree Predictors. | Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson |
| 2013 | UAI | Tighter Linear Program Relaxations for High Order Graphical Models. | Elad Mezuman, Daniel Tarlow, Amir Globerson, Yair Weiss |
| 2012 | ACL | Selective Sharing for Multilingual Dependency Parsing. | Tahira Naseem, Regina Barzilay, Amir Globerson |
| 2012 | EMNLP | Improved Parsing and POS Tagging Using Inter-Sentence Consistency Constraints. | Alexander M. Rush, Roi Reichart, Michael Collins, Amir Globerson |
| 2012 | EMNLP | Learning to Map into a Universal POS Tagset. | Yuan Zhang, Roi Reichart, Regina Barzilay, Amir Globerson |
| 2012 | ICML | Learning the Experts for Online Sequence Prediction. | Elad Eban, Aharon Birnbaum, Shai Shalev-Shwartz, Amir Globerson |
| 2011 | UAI | What Cannot be Learned with Bethe Approximations. | Uri Heinemann, Amir Globerson |
| 2010 | ICML | Learning Efficiently with Approximate Inference via Dual Losses. | Ofer Meshi, David A. Sontag, Tommi S. Jaakkola, Amir Globerson |
| 2009 | UAI | Convergent message passing algorithms - a unifying view. | Talya Meltzer, Amir Globerson, Yair Weiss |
| 2009 | UAI | Convexifying the Bethe Free Energy. | Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman |
| 2008 | UAI | Tightening LP Relaxations for MAP using Message Passing. | David A. Sontag, Talya Meltzer, Amir Globerson, Tommi S. Jaakkola, Yair Weiss |
| 2007 | EMNLP | Structured Prediction Models via the Matrix-Tree Theorem. | Terry Koo, Amir Globerson, Xavier Carreras, Michael Collins |
| 2007 | ICML | Exponentiated gradient algorithms for log-linear structured prediction. | Amir Globerson, Terry Koo, Xavier Carreras, Michael Collins |
| 2007 | UAI | Convergent Propagation Algorithms via Oriented Trees. | Amir Globerson, Tommi S. Jaakkola |
| 2006 | AAAI | Embedding Heterogeneous Data Using Statistical Models. | Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby |
| 2006 | ICML | Nightmare at test time: robust learning by feature deletion. | Amir Globerson, Sam T. Roweis |
| 2006 | UAI | Discriminative Learning via Semidefinite Probabilistic Models. | Koby Crammer, Amir Globerson |
| 2005 | AISTATS | Distributed Latent Variable Models of Lexical Co-occurrences. | John Blitzer, Amir Globerson, Fernando Pereira |
| 2004 | UAI | The Minimum Information Principle for Discriminative Learning. | Amir Globerson, Naftali Tishby |
| 2003 | UAI | Sufficient Dimensionality Reduction with Irrelevance Statistics. | Amir Globerson, Gal Chechik, Naftali Tishby |
| 2002 | AAAI | Most Informative Dimension Reduction. | Amir Globerson, Naftali Tishby |
| 2002 | ICML | Sufficient Dimensionality Reduction - A novel Analysis Method. | Amir Globerson, Naftali Tishby |