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Seong Joon Oh

Papers
37

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37papers

Authored papers

37

Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models

arXiv 2026

2026

MEME: Multi-entity & Evolving Memory Evaluation

arXiv 2026

2026

Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models

arXiv 2026

2026

When Do Diffusion Models learn to Generate Multiple Objects?

arXiv 2026

2026

It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs

arXiv 2026

2026

Privacy Collapse: Benign Fine-Tuning Can Break Contextual Privacy in Language Models

arXiv 2026

2026

Enhancing Multi-Image Understanding through Delimiter Token Scaling

arXiv 2026

2026

Half-Truths Break Similarity-Based Retrieval

arXiv 2026

2026

Does Data Scaling Lead to Visual Compositional Generalization?

arXiv 2025

2025

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers

arXiv 2025

2025

Diffusion Classifiers Understand Compositionality, but Conditions Apply

arXiv 2025

2025

Dr.LLM: Dynamic Layer Routing in LLMs

arXiv 2025

2025

On the rankability of visual embeddings

arXiv 2025

2025

CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally

arXiv 2025

2025

Are We Done with Object-Centric Learning?

arXiv 2025

2025

Calibrating Large Language Models Using Their Generations Only

arXiv 2024

2024

Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models

arXiv 2024

2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification

arXiv 2024

2024

Do Deep Neural Network Solutions Form a Star Domain?

arXiv 2024

2024

Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs

arXiv 2023

2023

Neglected Free Lunch -- Learning Image Classifiers Using Annotation Byproducts

arXiv 2023

2023

A Bayesian Approach To Analysing Training Data Attribution In Deep Learning

a-bayesian-approach-to-analysing-training

2023

Dataset Condensation via Efficient Synthetic-Data Parameterization

arXiv 2022

2022

Weakly Supervised Semantic Segmentation using Out-of-Distribution Data

CVPR 2022 1

2022

ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO

arXiv 2022

2022

SelecMix: Debiased Learning by Contradicting-pair Sampling

arXiv 2022

2022

Probabilistic Embeddings for Cross-Modal Retrieval

CVPR 2021 1

2021

Keep CALM and Improve Visual Feature Attribution

ICCV 2021 10

2021

Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels

CVPR 2021 1

2021

Rethinking Spatial Dimensions of Vision Transformers

ICCV 2021 10

2021

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights

adamp-slowing-down-the-slowdown-for-momentum

2020

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets

arXiv 2020

2020

Reliable Fidelity and Diversity Metrics for Generative Models

ICML 2020 1

2020

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

what-is-wrong-with-scene-text-recognition-1

2019

CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features

cutmix-regularization-strategy-to-train-1

2019

Learning De-biased Representations with Biased Representations

ICML 2020 1

2019

Modeling Uncertainty with Hedged Instance Embedding

arXiv 2018

2018

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from 37 papers