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Amir Globerson

100 papers · 2003–2026 · 18 conferences · across top CS/AI conferences

Achievements

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+17 more ↓ πŸ—ΊοΈ Taxonomy Completionist (24) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🌍 Conference Polyglot (18) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (14) 🌟 Keyword Trendsetter Combo (3) πŸ† Keyword Champion πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ’Ž Century Club (99) ❓ The Questioner (4) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (14) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (93)

Conferences

NIPS (19) ICML (18) EMNLP (11) ACL (9) AISTATS (8) ICLR (5) ECCV (4) JMLR (4) UAI (3) CONLL (3) EACL (3) NAACL (3) WACV (2) ICCV (2) CVPR (2) AAAI (2) IJCNLP (1) COLT (1)

Research topics

Papers

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