Chaithanya Kumar Mummadi
10 papers · 2019–2025 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
(8)
Learning Types Β· Machine Learning
(5)
Artificial Intelligence
(3)
Deep Learning
(3)
Application Areas
(3)
Core AI
(3)
Core Methods
(2)
Optimization & Theory
(2)
Techniques
(2)
Computer Vision
(1)
Analysis
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Processing
(1)
Keywords
vision-language model
(2)
image classification
(2)
semantic segmentation
(1)
shortcut learning
(1)
model robustness
(1)
semi-supervised learning
(1)
adversarial robustness
(1)
adversarial training
(1)
domain generalization
(1)
transfer learning
(1)
vision transformer
(1)
noisy label learning
(1)
self-supervised learning
(1)
data augmentation
(1)
contrastive learning
(1)
prompt learning
(1)
corruption robustness
(1)
neural network optimization
(1)
label noise
(1)
unsupervised learning
(1)
Papers
Visual Self-Refinement for Autoregressive Models
EMNLP 2025
Federated Text-driven Prompt Generation for Vision-Language Models
ICLR 2024
PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts
ICLR 2024
Give Me Your Attention: Dot-Product Attention Considered Harmful for Adversarial Patch Robustness
CVPR 2022
Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain
ECCV 2022
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization Opportunities
ICCV 2021
Does enhanced shape bias improve neural network robustness to common corruptions?
ICLR 2021
SELF: Learning to Filter Noisy Labels with Self-Ensembling
ICLR 2020
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision
NeurIPS 2019
Defending Against Universal Perturbations With Shared Adversarial Training
ICCV 2019