sDPO: Don't Use Your Data All at Once

no code implementations • 28 Mar 2024 • Dahyun Kim, Yungi Kim, Wonho Song, Hyeonwoo Kim, Yunsu Kim, Sanghoon Kim, Chanjun Park

As development of large language models (LLM) progresses, aligning them with human preferences has become increasingly important.

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

2 code implementations • 23 Dec 2023 • Dahyun Kim, Chanjun Park, Sanghoon Kim, Wonsung Lee, Wonho Song, Yunsu Kim, Hyeonwoo Kim, Yungi Kim, Hyeonju Lee, Jihoo Kim, Changbae Ahn, Seonghoon Yang, Sukyung Lee, Hyunbyung Park, Gyoungjin Gim, Mikyoung Cha, Hwalsuk Lee, Sunghun Kim

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.

Instruction Following Language Modelling +1

Interactive Multi-Class Tiny-Object Detection

1 code implementation • CVPR 2022 • Chunggi Lee, Seonwook Park, Heon Song, Jeongun Ryu, Sanghoon Kim, Haejoon Kim, Sérgio Pereira, Donggeun Yoo

We perform experiments on the Tiny-DOTA and LCell datasets using both two-stage and one-stage object detection architectures to verify the efficacy of our approach.

Feature Correlation Object +2

A community-powered search of machine learning strategy space to find NMR property prediction models

1 code implementation • 13 Aug 2020 • Lars A. Bratholm, Will Gerrard, Brandon Anderson, Shaojie Bai, Sunghwan Choi, Lam Dang, Pavel Hanchar, Addison Howard, Guillaume Huard, Sanghoon Kim, Zico Kolter, Risi Kondor, Mordechai Kornbluth, Youhan Lee, Youngsoo Lee, Jonathan P. Mailoa, Thanh Tu Nguyen, Milos Popovic, Goran Rakocevic, Walter Reade, Wonho Song, Luka Stojanovic, Erik H. Thiede, Nebojsa Tijanic, Andres Torrubia, Devin Willmott, Craig P. Butts, David R. Glowacki, Kaggle participants

The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions.

BIG-bench Machine Learning NMR J-coupling +1