27 citations · 59 across the 23 of their papers we have counts for
23 papers
String: An Agentic OS Where Every App Is a Markdown File
Jookyung Song, Nojun Kwak, Simyung Chang
LLM agents have become a new class of software user, but every surface they work through was designed for someone else. Pages are built for human eyes, which can skim and ignore; t…
Feature Diversification and Adaptation for Federated Domain Generalization
Seunghan Yang, Seokeon Choi, Hyunsin Park +3
Federated learning, a distributed learning paradigm, utilizes multiple clients to build a robust global model. In real-world applications, local clients often operate within their…
Crayon: Customized On-Device LLM via Instant Adapter Blending and Edge-Server Hybrid Inference
Jihwan Bang, Juntae Lee, Kyuhong Shim +2
The customization of large language models (LLMs) for user-specified tasks gets important. However, maintaining all the customized LLMs on cloud servers incurs substantial memory a…
Scalable Weight Reparametrization for Efficient Transfer Learning
Byeonggeun Kim, Jun-Tae Lee, Seunghan yang +1
This paper proposes a novel, efficient transfer learning method, called Scalable Weight Reparametrization (SWR) that is efficient and effective for multiple downstream tasks. Effic…
Quadapter: Adapter for GPT-2 Quantization
Minseop Park, Jaeseong You, Markus Nagel +1
Transformer language models such as GPT-2 are difficult to quantize because of outliers in activations leading to a large quantization error. To adapt to the error, one must use qu…
Personalized Keyword Spotting through Multi-task Learning
Seunghan Yang, Byeonggeun Kim, Inseop Chung +1
Keyword spotting (KWS) plays an essential role in enabling speech-based user interaction on smart devices, and conventional KWS (C-KWS) approaches have concentrated on detecting us…