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Sungjun Cho

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 11:22 PM AMS

8

papers

415

total citations

papers (8)

Pure Transformers are Powerful Graph Learners

NEURIPS 2022arXiv

Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers

Learning Equi-angular Representations for Online Continual Learning

Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs

Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning

Equivariant Hypergraph Neural Networks

Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost

NEURIPS 2022arXiv

3D Denoisers Are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation