Vaishaal Shankar
20 papers · 2019–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Academic Marathon (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (14)
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Cross-Pollinator
(14)
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Renaissance Researcher
(5)
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Taxonomy Completionist
(38)
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Mega-Team
(60)
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Dynamic Duo
(13)
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Triple Crown
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Topic Evolution
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Century Club
(20)
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Keyword Collector
(72)
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Unstoppable
(7)
β
The Questioner
(2)
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Prolific Year
(6)
Conferences
ICML (7)
NIPS (5)
ICLR (3)
ICCV (2)
ACL (1)
CVPR (1)
EMNLP (1)
Top co-authors
Keywords
image classification
(4)
distribution shift
(4)
transfer learning
(2)
contrastive learning
(2)
catastrophic forgetting
(2)
domain adaptation
(2)
domain generalization
(2)
image-text pair
(2)
data filtering
(2)
zero-shot learning
(1)
object recognition
(1)
neural tangent kernel
(1)
curriculum learning
(1)
video classification
(1)
feature space
(1)
out-of-distribution generalization
(1)
text-to-image generation
(1)
feature learning
(1)
multimodal learning
(1)
attention mechanism
(1)
Papers
Language models scale reliably with over-training and on downstream tasks
ICLR 2025
TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining
ACL 2025
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum
NIPS 2024
Scalable Pre-training of Large Autoregressive Image Models
ICML 2024
DataComp-LM: In search of the next generation of training sets for language models
NIPS 2024
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation
EMNLP 2024
TiC-CLIP: Continual Training of CLIP Models
ICLR 2024
Data Filtering Networks
ICLR 2024
Masked Autoencoding Does Not Help Natural Language Supervision at Scale
CVPR 2023
DataComp: In search of the next generation of multimodal datasets
NIPS 2023
Robustness in Multimodal Learning under Train-Test Modality Mismatch
ICML 2023
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)
ICML 2022
Predicting With Confidence on Unseen Distributions
ICCV 2021
Do Image Classifiers Generalize Across Time?
ICCV 2021
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
ICML 2021
Evaluating Machine Accuracy on ImageNet
ICML 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification
NIPS 2020
Neural Kernels Without Tangents
ICML 2020
A Meta-Analysis of Overfitting in Machine Learning
NIPS 2019
Do ImageNet Classifiers Generalize to ImageNet?
ICML 2019