most citedSOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

7 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

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…

cs.CV2026

Which Way Did It Move? Diagnosing and Overcoming Directional Motion Blindness in Video-LLMs

Jongseo Lee, Hyuntak Lee, Sunghun Kim +3

Video Large Language Models (Video-LLMs) have made rapid progress on temporal video understanding, yet many fail at a basic perceptual primitive: signed image-plane motion directio…

cs.CL2026

WebGen-R1: Incentivizing Large Language Models to Generate Functional and Aesthetic Websites with Reinforcement Learning

Juyong Jiang, Chenglin Cai, Chansung Park +4

While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic multi-page websites remain high…

cs.CL2026

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…

cs.CL2023★ 7 cited

SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Dahyun Kim, Chanjun Park, Sanghoon Kim +15

We introduce SOLAR 10.7B, a large language model (LLM) with 10.7 billion parameters, demonstrating superior performance in various natural language processing (NLP) tasks. Inspired…