48 citations · 93 across the 5 of their papers we have counts for
5 papers
TimelyRAG: Semantic-Temporal Hybrid Retrieval for Time-Critical Question Answering in Overlapping-Evolving Documents
Youngeun Nam, Joeun Kim, Hwanjun Song +3
Although large language models (LLMs) and retrieval-augmented generation (RAG) have advanced open-domain question answering (QA), they remain unreliable when documents evolve throu…
VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
Junhyeok Kang, Yooju Shin, Jae-Gil Lee
Variate tokenization, which independently embeds each variate as separate tokens, has achieved remarkable improvements in multivariate time series forecasting. However, employing s…
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream
Susik Yoon, Youngjun Lee, Jae-Gil Lee +1
Online anomaly detection from a data stream is critical for the safety and security of many applications but is facing severe challenges due to complex and evolving data streams fr…
Accurate and Fast Federated Learning via IID and Communication-Aware Grouping
Jin-woo Lee, Jaehoon Oh, Yooju Shin +2
Federated learning has emerged as a new paradigm of collaborative machine learning; however, it has also faced several challenges such as non-independent and identically distribute…
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
Jin-woo Lee, Jaehoon Oh, Sungsu Lim +2
Federated learning has emerged as a new paradigm of collaborative machine learning; however, many prior studies have used global aggregation along a star topology without much cons…