Amir Globerson

ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders EACL 2026 When Can Transformers Count to n? UAI 2026 DeciMamba: Exploring the Length Extrapolation Potential of Mamba ICLR 2025 Do LLMs have Consistent Values? ICLR 2025 Teaching Models to Improve on Tape AAAI 2025 EgoPet: Egomotion and Interaction Data from an Animal's Perspective ECCV 2024 Finding Visual Task Vectors ECCV 2024 Graph Neural Networks Use Graphs When They Shouldn’t ICML 2024 Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries EMNLP 2024 Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States ICML 2024 PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers Using Synthetic Scene Data WACV 2024 Provable Benefits of Complex Parameterizations for Structured State Space Models NeurIPS 2024 Stochastic positional embeddings improve masked image modeling ICML 2024 Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models NeurIPS 2024 TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools NeurIPS 2024 The Intelligible and Effective Graph Neural Additive Network NeurIPS 2024 TREE-G: Decision Trees Contesting Graph Neural Networks AAAI 2024 Visual Riddles: a Commonsense and World Knowledge Challenge for Large Vision and Language Models NeurIPS 2024 Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment ACL 2023 Crawling The Internal Knowledge-Base of Language Models EACL 2023 Dissecting Recall of Factual Associations in Auto-Regressive Language Models EMNLP 2023 In-Context Learning Creates Task Vectors EMNLP 2023 Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs EMNLP 2023 Learning Low Dimensional State Spaces with Overparameterized Recurrent Neural Nets ICLR 2023 LM vs LM: Detecting Factual Errors via Cross Examination EMNLP 2023 What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary ACL 2023 Active learning with label comparisons UAI 2022 Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens NeurIPS 2022 DETReg: Unsupervised Pretraining With Region Priors for Object Detection CVPR 2022 Efficient Learning of CNNs using Patch Based Features ICML 2022 Learning to Retrieve Passages without Supervision NAACL 2022 Object-Region Video Transformers CVPR 2022 On the Implicit Bias of Gradient Descent for Temporal Extrapolation AISTATS 2022 On the inductive bias of neural networks for learning read-once DNFs UAI 2022 Text-Only Training for Image Captioning using Noise-Injected CLIP EMNLP 2022 Visual Prompting via Image Inpainting NeurIPS 2022 An optimization and generalization analysis for max-pooling networks UAI 2021 A Theoretical Analysis of Fine-tuning with Linear Teachers NeurIPS 2021 BERTese: Learning to Speak to BERT EACL 2021 Compositional Video Synthesis with Action Graphs ICML 2021 Explaining in Style: Training a GAN To Explain a Classifier in StyleSpace ICCV 2021 Few-Shot Question Answering by Pretraining Span Selection ACL 2021 On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent ICML 2021 Towards Understanding Learning in Neural Networks with Linear Teachers ICML 2021 A Simple and Effective Model for Answering Multi-span Questions EMNLP 2020 Differentiable Scene Graphs WACV 2020 Learning Canonical Representations for Scene Graph to Image Generation ECCV 2020 Learning Object Permanence from Video ECCV 2020 Optimal Strategies Against Generative Attacks ICLR 2020 Pre-training Mention Representations in Coreference Models EMNLP 2020 Regularizing Towards Permutation Invariance In Recurrent Models NeurIPS 2020 Coreference Resolution with Entity Equalization ACL 2019 Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing NAACL 2019 Learning Rules-First Classifiers AISTATS 2019 Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem ICML 2019 Learning to Optimize Combinatorial Functions ICML 2018 Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction NeurIPS 2018 Predict and Constrain: Modeling Cardinality in Deep Structured Prediction ICML 2018 Semi-Supervised Learning with Competitive Infection Models AISTATS 2018 SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data ICLR 2018 Weakly Supervised Semantic Parsing with Abstract Examples ACL 2018 Effective Semisupervised Learning on Manifolds COLT 2017 Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs ICML 2017 Learning Infinite Layer Networks Without the Kernel Trick ICML 2017 Robust Conditional Probabilities NeurIPS 2017 Collective Entity Resolution with Multi-Focal Attention ACL 2016 Improper Deep Kernels AISTATS 2016 Optimal Tagging with Markov Chain Optimization NeurIPS 2016 How Hard is Inference for Structured Prediction? ICML 2015 Template Kernels for Dependency Parsing NAACL 2015 Discrete Chebyshev Classifiers ICML 2014 Efficient Lifting of MAP LP Relaxations Using k-Locality AISTATS 2014 Inferning with High Girth Graphical Models ICML 2014 Learning Structured Models with the AUC Loss and Its Generalizations AISTATS 2014 Spectral Regularization for Max-Margin Sequence Tagging ICML 2014 Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees ACL 2014 Higher Order Matching for Consistent Multiple Target Tracking ICCV 2013 The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification ICML 2013 Transfer Learning for Constituency-Based Grammars ACL 2013 Vanishing Component Analysis ICML 2013 A Simple Geometric Interpretation of SVM using Stochastic Adversaries AISTATS 2012 Convergence Rate Analysis of MAP Coordinate Minimization Algorithms NeurIPS 2012 Improved Parsing and POS Tagging Using Inter-Sentence Consistency Constraints EMNLP 2012 Learning to Map into a Universal POS Tagset EMNLP 2012 Selective Sharing for Multilingual Dependency Parsing ACL 2012 Learning Bayesian Network Structure using LP Relaxations AISTATS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010 An LP View of the M-best MAP problem NeurIPS 2009 Clusters and Coarse Partitions in LP Relaxations NeurIPS 2008 Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks JMLR 2008 Convex Learning with Invariances NeurIPS 2007 Euclidean Embedding of Co-occurrence Data JMLR 2007 Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations NeurIPS 2007 Structured Prediction Models via the Matrix-Tree Theorem EMNLP 2007 Approximate inference using planar graph decomposition NeurIPS 2006 Information Bottleneck for Gaussian Variables JMLR 2005 Sufficient Dimensionality Reduction JMLR 2003 Approximate inference using conditional entropy decompositions AISTATS 1999 Visualizing pairwise similarity via semidefinite programming AISTATS 1999