Zobrazeno 1 - 10
of 84
pro vyhledávání: '"Song, Wonho"'
Autor:
Oh, Minho, Shin, Gunhee, Jang, Seoyeon, Lee, Seungjae, Lee, Dongkyu, Song, Wonho, Yu, Byeongho, Lim, Hyungtae, Lee, Jaeyoung, Myung, Hyun
Recognizing traversable terrain from 3D point cloud data is critical, as it directly impacts the performance of autonomous navigation in off-road environments. However, existing segmentation algorithms often struggle with challenges related to change
Externí odkaz:
http://arxiv.org/abs/2406.18138
With the rapid development of autonomous driving and SLAM technology, the performance of autonomous systems using multimodal sensors highly relies on accurate extrinsic calibration. Addressing the need for a convenient, maintenance-friendly calibrati
Externí odkaz:
http://arxiv.org/abs/2406.11599
This paper introduces Evalverse, a novel library that streamlines the evaluation of Large Language Models (LLMs) by unifying disparate evaluation tools into a single, user-friendly framework. Evalverse enables individuals with limited knowledge of ar
Externí odkaz:
http://arxiv.org/abs/2404.00943
Autor:
Kim, Dahyun, Kim, Yungi, Song, Wonho, Kim, Hyeonwoo, Kim, Yunsu, Kim, Sanghoon, Park, Chanjun
As development of large language models (LLM) progresses, aligning them with human preferences has become increasingly important. We propose stepwise DPO (sDPO), an extension of the recently popularized direct preference optimization (DPO) for alignm
Externí odkaz:
http://arxiv.org/abs/2403.19270
Autor:
Kim, Dahyun, Park, Chanjun, Kim, Sanghoon, Lee, Wonsung, Song, Wonho, Kim, Yunsu, Kim, Hyeonwoo, Kim, Yungi, Lee, Hyeonju, Kim, Jihoo, Ahn, Changbae, Yang, Seonghoon, Lee, Sukyung, Park, Hyunbyung, Gim, Gyoungjin, Cha, Mikyoung, Lee, Hwalsuk, Kim, Sunghun
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 by recent efforts to efficiently up-scale LLMs, we present a method f
Externí odkaz:
http://arxiv.org/abs/2312.15166
Autor:
Song, Wonho, Lee, Jung-Yong, Kim, Junhyung, Park, Jinyoung, Jo, Jaehyeong, Hyun, Eunseok, Kim, Jiwan, Eom, Daejin, Choi, Gahyun, Park, Kibog
The effective work-function of metal electrode is one of the major factors to determine the threshold voltage of metal/oxide/semiconductor junction. In this work, we demonstrate experimentally that the effective work-function of Aluminum (Al) electro
Externí odkaz:
http://arxiv.org/abs/2208.08044
Autor:
Oh, Minho, Jung, Euigon, Lim, Hyungtae, Song, Wonho, Hu, Sumin, Lee, Eungchang Mason, Park, Junghee, Kim, Jaekyung, Lee, Jangwoo, Myung, Hyun
Perception of traversable regions and objects of interest from a 3D point cloud is one of the critical tasks in autonomous navigation. A ground vehicle needs to look for traversable terrains that are explorable by wheels. Then, to make safe navigatio
Externí odkaz:
http://arxiv.org/abs/2206.03190
Trigger set-based watermarking schemes have gained emerging attention as they provide a means to prove ownership for deep neural network model owners. In this paper, we argue that state-of-the-art trigger set-based watermarking algorithms do not achi
Externí odkaz:
http://arxiv.org/abs/2106.10147
A community-powered search of machine learning strategy space to find NMR property prediction models
Autor:
Bratholm, Lars A., Gerrard, Will, Anderson, Brandon, Bai, Shaojie, Choi, Sunghwan, Dang, Lam, Hanchar, Pavel, Howard, Addison, Huard, Guillaume, Kim, Sanghoon, Kolter, Zico, Kondor, Risi, Kornbluth, Mordechai, Lee, Youhan, Lee, Youngsoo, Mailoa, Jonathan P., Nguyen, Thanh Tu, Popovic, Milos, Rakocevic, Goran, Reade, Walter, Song, Wonho, Stojanovic, Luka, Thiede, Erik H., Tijanic, Nebojsa, Torrubia, Andres, Willmott, Devin, Butts, Craig P., Glowacki, David R., participants, Kaggle
The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in adva
Externí odkaz:
http://arxiv.org/abs/2008.05994
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