← Authors

Amir Globerson

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

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (24) πŸƒ Academic Marathon (22) 🧭 Keyword Pioneer 🐣 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)

Top co-authors

Trevor Darrell (11) Jonathan Berant (10) Amir Bar (9) Gal Chechik (9) Roei Herzig (9) Alon Brutzkus (8) Gal Elidan (7) Regina Barzilay (6) Ori Ram (5) Tommi S. Jaakkola (5)

Research topics

Education (1)

Keywords

graphical model (8) structured prediction (7) sample complexity (5) zero-shot learning (5) combinatorial optimization (5) semi-supervised learning (5) gradient descent (4) lp relaxation (4) linear programming relaxation (4) question answering (4) large language model (4) action recognition (4) feature learning (4) map inference (4) convolutional neural network (4) probabilistic inference (3) unsupervised learning (3) scene graph (3) representation learning (3) few-shot learning (3)

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