Jongwoo Ko
15 papers · 2021–2025 · 8 venues · across top CS/AI venues
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noisy label
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label noise
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vision-language model
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data augmentation
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knowledge distillation
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prompt learning
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machine translation
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Papers
Bayesian Principles Improve Prompt Learning In Vision-Language Models
AISTATS 2025
Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge
ICLR 2025
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs
ICML 2025
SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins
ICLR 2025
DistiLLM: Towards Streamlined Distillation for Large Language Models
ICML 2024
Fine-tuning Pre-trained Models for Robustness under Noisy Labels
IJCAI 2024
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models
EMNLP 2024
A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise
AAAI 2023
CUDA: Curriculum of Data Augmentation for Long-tailed Recognition
ICLR 2023
Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding
EMNLP 2023
NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
EMNLP 2023
Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective
EACL 2023
Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network
AAAI 2023
Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks
EMNLP 2022
FINE Samples for Learning with Noisy Labels
NeurIPS 2021