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Minseok Kim 
Biography
I am a senior research scientist at Meta, working on enhancing LLM-based assistant service quality. Before Meta, I was at Amazon AGI as an Applied Scientist II to advance the next-generation Alexa powered by LLM. My expertise spans extensive experience in designing, training, and evaluating LLM models, complemented by a proven track record in developing sophisticated pipelines aimed at continually enhancing performance.
Interests
- Large Language Model based Conversational AI
- Recommendation System
- Information Retrieval
- Trustworthy ML
- Real-World ML/AI Challenges
Education
PhD in Graduate School of Data Science
Korea Advanced Institute of Science and Technology (KAIST)
Recent Publications
Quickly discover relevant content by filtering publications.
Aligning Large Language Models via Fine-grained Supervision (ACL 2024)
Pre-trained large-scale language models (LLMs) excel at producing coherent articles, yet their outputs may be untruthful, toxic, or …
Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise (AAAI 2024)
Multi-label classification poses challenges due to imbalanced and noisy labels in training data. We propose a unified data augmentation …
Debiasing Neighbor Aggregation for Graph Neural Network in Recommender Systems (CIKM 2022)
Graph neural networks (GNNs) have achieved remarkable success in recommender systems by representing users and items based on their …
Learning from Noisy Labels with Deep Neural Networks: A Survey (TNNLS 2022)
Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of …
Meta-Learning for Online Update of Recommender Systems (AAAI 2022)
Online recommender systems should be always aligned with users' current interest to accurately suggest items that each user would like. …
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies (AAAI 2022)
Assessing the impact of the COVID-19 crisis on economies is fundamental to tailor the responses of the governments to recover from the …
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data (NeurIPS 2021)
A deep neural network (DNN) has achieved great success in many machine learning tasks by virtue of its high expressive power. However, …
Robust Learning by Self-Transition for Handling Noisy Labels (KDD 2021)
Real-world data inevitably contains noisy labels, which induce the poor generalization of deep neural networks. It is known that the …
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation (AAAI 2021)
Point-of-interest (POI) recommendation has become an important research topic in these days. The user check-in history used as the …
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection (CIKM 2020)
The performance of deep neural networks is significantly affected by how well mini-batches are constructed. In this paper, we propose a …
Ada-Boundary: Accelerating DNN Training via Adaptive Boundary Batch Selection (Machine Learning 2020, (SCI Expanded, impact factor: 2.672)
Neural networks converge faster with help from a smart batch selection strategy. In this regard, we propose Ada-Boundary, a novel and …
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea (KDD 2020)
The escalating crisis of COVID-19 has put people all over the world in danger. Owing to the high contagion rate of the virus, COVID-19 …
How Does Early Stopping Help Generalization against Label Noise? (ICMLW 2020)
Noisy labels are very common in real-world training data, which lead to poor generalization on test data because of overfitting to the …
News
Lectures & Mentoring
Special AI Academy Program AI-based Project Mentor
Seocho-gu office, Korea
Jul 2022
– Sep 2022
Project Mentor
Special AI Academy Program AI-based Project Mentor
Seocho-gu office, Korea
Aug 2021
– Sep 2021
Project Mentor
Special AI Academy Program (Stage 4: AI-based project)
Seocho-gu office, Korea
Sep 2019
– Dec 2019
Project Mentor
Special AI Academy Program (Stage 2: Data Structure & Algorithm)
Seocho-gu office, Korea
Jul 2019
Lecturer
Contact
- minseokkim0630@gmail.com
- 10301 Willows Rd NE, Redmond, Washington 98052
- Redmond X