Yeachan Kim
20 papers · 2018–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (6) π Cross-Pollinator (8)
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Taxonomy Completionist
(50)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π§¬
Topic Evolution
π€
Dynamic Duo
(18)
β‘
Prolific Year
(8)
π
Century Club
(20)
ποΈ
Keyword Collector
(107)
Conferences
EMNLP (9)
ACL (7)
AAAI (1)
COLING (1)
MLHC (1)
UAI (1)
Top co-authors
Keywords
model compression
(4)
parameter-efficient fine-tuning
(4)
efficient computing
(2)
pre-trained language model
(2)
representation learning
(2)
knowledge transfer
(2)
out-of-distribution generalization
(2)
natural language understanding
(2)
memory efficiency
(2)
convolutional neural network
(2)
contrastive learning
(2)
materials science
(2)
curriculum learning
(2)
transformer architecture
(2)
molecular property prediction
(2)
language model adaptation
(2)
embedding learning
(1)
text classification
(1)
domain adaptation
(1)
zero-shot learning
(1)
Papers
Forward Knows Efficient Backward Path: Saliency-Guided Memory-Efficient Fine-tuning of Large Language Models
ACL 2025
Curriculum Debiasing: Toward Robust Parameter-Efficient Fine-Tuning Against Dataset Biases
ACL 2025
Bridging the Gap Between Molecule and Textual Descriptions via Substructure-aware Alignment
EMNLP 2025
SEED: Semantic Knowledge Transfer for Language Model Adaptation to Materials Science
EMNLP 2024
SparseFlow: Accelerating Transformers by Sparsifying Information Flows
ACL 2024
Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning
ACL 2024
Zero-shot Commonsense Reasoning over Machine Imagination
EMNLP 2024
MELT: Materials-aware Continued Pre-training for Language Model Adaptation to Materials Science
EMNLP 2024
KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters
ACL 2024
MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction
EMNLP 2024
Moleco: Molecular Contrastive Learning with Chemical Language Models for Molecular Property Prediction
EMNLP 2024
Phase-shifted adversarial training
UAI 2023
Client-Customized Adaptation for Parameter-Efficient Federated Learning
ACL 2023
Improving Bias Mitigation through Bias Experts in Natural Language Understanding
EMNLP 2023
Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing
EMNLP 2023
Dynamic Structure Pruning for Compressing CNNs
AAAI 2023
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention
MLHC 2021
Adaptive Compression of Word Embeddings
ACL 2020
Multi-pretraining for Large-scale Text Classification
EMNLP 2020
Learning to Generate Word Representations using Subword Information
COLING 2018