Saurabh Garg
24 papers · 2018–2024 · 6 conferences · across top CS/AI conferences
Achievements
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Prolific Year
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Conferences
NIPS (11)
ICML (5)
ICLR (4)
EMNLP (2)
ACL (1)
INTERSPEECH (1)
Top co-authors
Keywords
distribution shift
(6)
domain adaptation
(5)
language model
(4)
label shift
(3)
zero-shot learning
(2)
unsupervised learning
(2)
large language model
(2)
semi-supervised learning
(2)
reinforcement learning
(2)
neural network
(2)
ensemble learning
(1)
transfer learning
(1)
double descent
(1)
bayesian inference
(1)
image classification
(1)
model selection
(1)
prompt engineering
(1)
few-shot learning
(1)
speech recognition
(1)
hyperparameter optimization
(1)
Papers
TiC-CLIP: Continual Training of CLIP Models
ICLR 2024
Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress?
EMNLP 2024
DataComp-LM: In search of the next generation of training sets for language models
NIPS 2024
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
NIPS 2024
Post-Hoc Reversal: Are We Selecting Models Prematurely?
NIPS 2024
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models
ICML 2024
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets
ICML 2023
Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
NIPS 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
NIPS 2023
Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
NIPS 2023
Downstream Datasets Make Surprisingly Good Pretraining Corpora
ACL 2023
Disentangling the Mechanisms Behind Implicit Regularization in SGD
ICLR 2023
Deconstructing Distributions: A Pointwise Framework of Learning
ICLR 2023
RLSbench: Domain Adaptation Under Relaxed Label Shift
ICML 2023
Domain Adaptation under Open Set Label Shift
NIPS 2022
Unsupervised Learning under Latent Label Shift
NIPS 2022
Characterizing Datapoints via Second-Split Forgetting
NIPS 2022
Leveraging unlabeled data to predict out-of-distribution performance
ICLR 2022
Mixture Proportion Estimation and PU Learning:A Modern Approach
NIPS 2021
On Proximal Policy Optimizationβs Heavy-tailed Gradients
ICML 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization
ICML 2021
A Unified View of Label Shift Estimation
NIPS 2020
Dual Language Models for Code Switched Speech Recognition
INTERSPEECH 2018
Code-switched Language Models Using Dual RNNs and Same-Source Pretraining
EMNLP 2018