Amir Globerson
100 papers · 2003–2026 · 18 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (24) π§ Keyword Pioneer π Renaissance Researcher (6) π Interdisciplinary Bridge π£ Hot Topic Early Bird
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Conference Polyglot
(18)
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Renaissance Researcher
(6)
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Cross-Pollinator
(14)
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Keyword Trendsetter Combo
(3)
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Keyword Champion
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Triple Crown
π±
Topic Pioneer
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Deep Specialist
(10)
π€
Dynamic Duo
(11)
π
Grand Slam
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Century Club
(99)
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The Questioner
(4)
π
Trend Setter
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Conference Pioneer
π₯
Unstoppable
(14)
β‘
Prolific Year
(7)
ποΈ
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
Research topics
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 Shouldnβt
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