3 citations · 3 across the 7 of their papers we have counts for
7 papers
Solar Open 2 Technical Report
Sungrae Park, Sanghoon Kim, Gyoungjin Gim +50
We present Solar Open 2, a 250B-A15B Mixture-of-Experts language model built for long-horizon agentic tasks, scaled up from Solar Open 1 (Solar Open 100B). To hold entire agent tra…
Cross-lingual Retrieval-Augmented Classification for Dysarthria Severity Assessment
Taeyoung Jeong, Insung Lee, Du-Seong Chang +1
Automatic dysarthria severity assessment is limited by the scarcity of labeled pathological speech data. To address this, we propose Cross-lingual Retrieval-Augmented Classificatio…
Solar Open Technical Report
Sungrae Park, Sanghoon Kim, Jungho Cho +34
We introduce Solar Open, a 102B-parameter bilingual Mixture-of-Experts language model for underserved languages. Solar Open demonstrates a systematic methodology for building compe…
Towards Fast Multilingual LLM Inference: Speculative Decoding and Specialized Drafters
Euiin Yi, Taehyeon Kim, Hongseok Jeung +2
Large language models (LLMs) have revolutionized natural language processing and broadened their applicability across diverse commercial applications. However, the deployment of th…
How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Hoyeon Chang, Jinho Park, Seonghyeon Ye +4
Despite the recent observation that large language models (LLMs) can store substantial factual knowledge, there is a limited understanding of the mechanisms of how they acquire fac…
ExeGPT: Constraint-Aware Resource Scheduling for LLM Inference
Hyungjun Oh, Kihong Kim, Jaemin Kim +4
This paper presents ExeGPT, a distributed system designed for constraint-aware LLM inference. ExeGPT finds and runs with an optimal execution schedule to maximize inference through…
NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models
Jongwoo Ko, Seungjoon Park, Yujin Kim +4
Structured pruning methods have proven effective in reducing the model size and accelerating inference speed in various network architectures such as Transformers. Despite the vers…