781 to 790 of 3,555 Results
May 22, 2025 - S-Lab for Advanced Intelligence
Xu, Qianxiong; Zhu, Lanyun; Liu, Xuanyi; Lin, Guosheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "Unlocking the Power of SAM 2 for Few-Shot Segmentation", https://doi.org/10.21979/N9/XIDXVT, DR-NTU (Data), V1
Few-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use the well-learned knowledge of foundation models (e.g., SAM) to simplify the learning process. Recen... |
May 20, 2025 - TAN Fangyi
Tan, Fangyi; Samanta, Dhrubajyoti, 2025, "Replication Data for: Reconciling record-breaking ocean temperatures within the Singapore Strait in 2023 with satellite and in-situ data", https://doi.org/10.21979/N9/HEXBWR, DR-NTU (Data), V1, UNF:6:Cl3gQnI/p2qdkYLRycqjDQ== [fileUNF]
This dataset contains the supplementary files and data that were used to produce the manuscript titled: "Reconciling record-breaking ocean temperatures within the Singapore Strait in 2023 with satellite and in-situ data". |
May 16, 2025 - S-Lab for Advanced Intelligence
Liu, Chenxi; Miao, Hao; Xu, Qianxiong; Zhou, Shaowen; Long, Cheng; Zhao, Yan; Li, Ziyue, 2025, "Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation", https://doi.org/10.21979/N9/6WWC6K, DR-NTU (Data), V1
Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements in large language models (LLMs), recent studies employ textual prompt tuning to infuse the... |
Bauer, Ute Meta, 2025, "Climate Crisis and Cultural Loss Exhibition", https://doi.org/10.21979/N9/Y0XINX, DR-NTU (Data), V2
NTU Centre for Contemporary Art Singapore (NTU CCA Singapore) presents the two-part research presentation Climate Crisis and Cultural Loss. First unfolding at TBA21–Academy’s Ocean Space in Venice, Italy, the research inquiry later materialises in another configuration at ADM Gal... |
May 13, 2025 - S-Lab for Advanced Intelligence
Liu, Chenxi; Zhou, Shaowen; Xu, Qianxiong; Miao, Hao; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era", https://doi.org/10.21979/N9/I0HOYZ, DR-NTU (Data), V1
The proliferation of edge devices has generated an unprecedented volume of time series data across different domains, motivating various well-customized methods. Recently, Large Language Models (LLMs) have emerged as a new paradigm for time series analytics by leveraging the shar... |
May 9, 2025 - S-Lab for Advanced Intelligence
Dong, Yuhao; Liu, Zuyan; Sun, Hai-Long; Yang, Jingkang; Hu, Winston; Rao, Yongming; Liu, Ziwei, 2025, "Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models", https://doi.org/10.21979/N9/Y0TZUB, DR-NTU (Data), V1
Large Language Models (LLMs) demonstrate enhanced capabilities and reliability by reasoning more, evolving from Chain-of-Thought prompting to product-level solutions like OpenAI o1. Despite various efforts to improve LLM reasoning, high-quality long-chain reasoning data and optim... |
May 9, 2025 - S-Lab for Advanced Intelligence
Huang, Zihao; Hu, Shoukang; Wang, Guangcong; Liu, Tianqi; Zang, Yuhang; Cao, Zhiguo; Li, Wei; Liu, Ziwei, 2025, "WildAvatar: Learning In-the-wild 3D Avatars from the Web", https://doi.org/10.21979/N9/5G18B1, DR-NTU (Data), V1
Existing research on avatar creation is typically limited to laboratory datasets, which require high costs against scalability and exhibit insufficient representation of the real world. On the other hand, the web abounds with off-the-shelf real-world human videos, but these video... |
Sarkawi, Gina M.; Meltzner, Aron J.; Peng Dongju; Lim, Joanne T.Y.; Li Xinnan; Gautam, Rohan; Gopal, Anandh; Mitchell, Andrew; Sarmiento, Loraine Faye; Weil-Accardo, Jennifer; Maxwell, Kathrine V.; Komori, Junki; Ramos, Noelynna T., 2025, "Replication Data for: A coral microatoll record of sea-level rise, interseismic deformation, and El Niño in La Union, Philippines since 1906 CE", https://doi.org/10.21979/N9/32SKMK, DR-NTU (Data), V1, UNF:6:fmVl46oGMLCgrUwL6sQ24Q== [fileUNF]
Field data (field notes, field photos, slab photos, raw x-ray images, annotated slab mosaics, survey files), time series, coral tilt correction, tide-gauge data and the associated files and scripts for determining tides and reconstructing water level. |
