The archive of workshops

2026/02/27 Progress Workshop

• 희문 | A single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings 

• 채영 | Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding

2026/02/23 Joint Workshop with IDEA Lab@KU

• 윤환 | SIMBAD: Spatio-Temporal Traffic Forecasting Robust to Aperiodicity

• 승한 | Recent work on Recommender System 

• 명준 | Boosting Autoencoders via Latent Density-aware Sampling for Unsupervised Anomaly Detection 

• 제윤 | Recent work on Scientific Document Retrieval 

2025/09~12 Fall Seminar

• 09/29 희정 | Towards Knowledge Base Distillation for SLM Fine-Grained Reasoning

• 10/27 현웅 | Maximizing Profit through Smart Targeting: Predicting Who Will Buy

• 11/10 우준 | 지난 연구를 통해 얻은 것

• 11/17 예빈 | EMNLP 학회 참관기

• 11/24 선호 | Mixture of Experts Strategy for Multimodal Time Series 

• 12/01 현구 | How Can We Structure Knowledge for Effective RAG?

• 12/09 지효 | The Grain on the Scale: Model in Problem, Problem in Model

• 12/22 윤환 | From Graph to GNNs

2025/08/27 Joint Workshop with IDEA Lab@KU

• 현구 | MGRank: Unsupervised Keyphrase Extraction with Multi-granular Topic Saliency

• 수빈 | Semantic-Aware Vertical Partitioning for Efficient Table Retrieval

• 예빈 | Multi-level Diagnosis and Evaluation for Robust Tabular Feature Engineering with Large Language Models 

2025/08/25 Progress Workshop

• 현웅 | Dissecting Channel Dependency in Multivariate Time Series Forecasting: Interaction Scope, Level, and Architecture 

• 윤환 | Aperiodicity-Robust Spatio-Temporal Traffic Forecasting 

• 지연 | Value-aware Cross-Modal Alignment: Learning Numeric-Semantic Representations between Text and Time-Series 

• 주형 | Systematic Literature Review of Online Deep Anomaly Detection

• 명준 | Online Anomaly Detection via Adaptive Boosting with Dynamic Weighting 

• 선호 | Causal Differential Equation Model for Anomaly Detection in Time Series

• 지효 | AI for Biomedical Challenges: From Literature Insights to Real-world Applications 

• 우준 | Representation Learning: From Foundations to Structured Abstractions in Tabular Data 

• 연우 | Leveraging Intra-Column Relationships for Enhanced Table Understanding 

• 승원 | Overcoming Local Sparsity in Continual Knowledge Graph Learning 

• 희정 | Continual Retrieval on Dynamic Streaming Corpora with Adaptive Soft Memory 

• 원준 | Persona-adaptive Memory Module for LLM-based Agents 

• 현직 | Soft Prompt–driven Multitask Learning with Task Group Adaptation 

• 민열 | From Forgetting to Improvement: Continual GraphRAG for Multi-hop QA 

• 예림 | Tool-Augmented Context Engineering for Hybrid KV-Cache Management in AI Agents 

2025/02/27 Progress Workshop

• 수빈 | Open-world machine learning and retrieval-enhanced tabular prediction 

• 명준 | Concept-drifted world and retrieval-enhanced tabular anomaly detection 

• 승원 | Knowledge graph for/from large language models

• 원준 | Large language model to perceive, memorize, and act

2024/11/29 Progress Workshop

• 현구 | Keyword extraction with multi-granular topic saliency 

• 지효 | Textual and visual understanding of Organ-on-a-Chip research 

• 희정 | Continual retrieval on dynamic streaming corpora

• 민혁 | Query-to-columns for human-like table retrieval system 

• 우준 | Dynamic exploitation of tabular data by leveraging semi-structured knowledge

• 연우 | InterCellFormer: leveraging intra-column relationships for enhanced table understanding 

• 예빈 | Towards robust feature engineering with large language models 

• 지연 | Interpretable prototype: a bridge from text to time-series for LLM 

• 현웅 | Dissecting dependencies in multi-channel time series forecasting

• 윤환 | Spatio-temporal prediction with graph neural network 

• 선호 | Look-ahead augmentation for time-series forecasting 

• 주형 | Recent trends and frontiers of online deep anomaly detection

• [Invited Talk] 유경 | Towards goal-oriented language intelligence with robust evaluation