Jaehyung Kim

Affiliations:
  • Yonsei University , Korea
  • Carnegie Mellon University, PA, USA


According to our database1, Jaehyung Kim authored at least 27 papers between 2017 and 2024.

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Bibliography

2024
Tabular Transfer Learning via Prompting LLMs.
CoRR, 2024

DEF-oriCORN: efficient 3D scene understanding for robust language-directed manipulation without demonstrations.
CoRR, 2024

Few-shot Personalization of LLMs with Mis-aligned Responses.
CoRR, 2024

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning.
CoRR, 2024

Aligning Large Language Models with Self-generated Preference Data.
CoRR, 2024

Online Adaptation of Language Models with a Memory of Amortized Contexts.
CoRR, 2024

SelectLLM: Can LLMs Select Important Instructions to Annotate?
CoRR, 2024

Under the Surface: Tracking the Artifactuality of LLM-Generated Data.
CoRR, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.
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Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning to Correct for QA Reasoning with Black-box LLMs.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Meta-Crafting: Improved Detection of Out-of-Distributed Texts via Crafting Metadata Space (Student Abstract).
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Annotation Imputation to Individualize Predictions: Initial Studies on Distribution Dynamics and Model Predictions.
Proceedings of the 2nd Workshop on Perspectivist Approaches to NLP co-located with 26th European Conference on Artificial Intelligence (ECAI 2023), 2023

Pre-and Post-Contact Policy Decomposition for Non-Prehensile Manipulation with Zero-Shot Sim-To-Real Transfer.
IROS, 2023

Prefer to Classify: Improving Text Classifiers via Auxiliary Preference Learning.
Proceedings of the International Conference on Machine Learning, 2023

RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Everyone's Voice Matters: Quantifying Annotation Disagreement Using Demographic Information.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Time Is MattEr: Temporal Self-supervision for Video Transformers.
Proceedings of the International Conference on Machine Learning, 2022

Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

What Makes Better Augmentation Strategies? Augment Difficult but Not too Different.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Patch-level Representation Learning for Self-supervised Vision Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

M2m: Imbalanced Classification via Major-to-Minor Translation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2017
Simplified Stochastic Feedforward Neural Networks.
CoRR, 2017


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