1 to 10 of 233 Results
Apr 28, 2026 - S-Lab for Advanced Intelligence
Xu, Yuanmu; Hou, Guanli; Hu, Jiangbei; Ren, Tenglong; Wang, Xiaokun; Zhang, Yalan; Ban, Xiaojuan; Qian, Chen; Hou, Fei; He, Ying, 2025, "PGA-NeuS: Physics and Geometry-Augmented Neural Implicit Surfaces for Rigid Bodies", https://doi.org/10.21979/N9/LTXKFL, DR-NTU (Data), V2
This paper tackles the challenges of physics-based simulation of rigid bodies in neural rendering, focusing on 3D model representation and collision handling. A synthetic and real-world dataset is also included in the paper. |
Apr 7, 2026 - Luo Xiangzhong
Luo, Xiangzhong; Liu, Weichen, 2026, "Replication Data for: Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems", https://doi.org/10.21979/N9/VVAKSR, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper "Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems", accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and S... |
Apr 7, 2026 - Luo Xiangzhong
Luo, Xiangzhong; Liu, Di; Kong, Hao; Huai, Shuo; Liu, Weichen, 2026, "Replication Data for: Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems", https://doi.org/10.21979/N9/BIOGHZ, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper "Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems" |
Mar 13, 2026 - Other Projects of the Liu Team
Wu, Ting; Long, Linbo; Ma, Zhulin; Yu, Qiushuang; Tian, Hang; Liu, Weichen, 2026, "Replication Data for: Simulating CXL Shared Coherent Memory Using Shared Memory Among Virtual Machines", https://doi.org/10.21979/N9/BUO9DY, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper "Simulating CXL Shared Coherent Memory Using Shared Memory Among Virtual Machines" |
Mar 2, 2026 - Guochu XIONG
Xiong, Guochu, 2026, "Replication Data for: Coherence-Aware Task Graph Modeling for Realistic Application", https://doi.org/10.21979/N9/PZIE8J, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper 'Coherence-Aware Task Graph Modeling for Realistic Application'. |
Jan 30, 2026 - PREMANAND Rithwik
Jose, Justin; Premanand, Rithwik; Vishwakarma, Narendra; Madhukumar, A. S., 2026, "Replication Data for: Multi-Pair Full-Duplex D2D with RIS Partitioning: Performance Analysis and Optimization", https://doi.org/10.21979/N9/H1TOEE, DR-NTU (Data), V1
Replication Data for: Multi-Pair Full-Duplex D2D with RIS Partitioning: Performance Analysis and Optimization |
Jan 30, 2026 - PREMANAND Rithwik
Premanand, Rithwik, 2026, "RIS-Enhanced Hybrid THz/RF Systems for 6G Networks Over Generalized Fading", https://doi.org/10.21979/N9/X310LF, DR-NTU (Data), V1
This dataset contains MATLAB simulation scripts and supporting functions for analyzing the performance of Reconfigurable Intelligent Surfaces (RIS)-assisted hybrid Terahertz (THz) and Radio Frequency (RF) communication systems operating over generalized fading channels. The simul... |
Li, Miaoyu; Chao, Qin; Li, Boyang, 2025, "Replication Data for: Two Causally Related Needles in a Video Haystack", https://doi.org/10.21979/N9/WCSXMT, DR-NTU (Data), V2
Causal2Needles is a benchmark dataset and evaluation toolkit designed to assess the capabilities of both proprietary and open-source multimodal large language models in long-video understanding. It features a large number of "2-needle" questions, where the model must locate and r... |
Dec 10, 2025 - Junqi ZHAO
Chinchure, Aditya; Ravi, Sahithya; Ng, Raymond; Shwartz, Vered; Li, Boyang; Sigal, Leonid, 2025, "Replication Data for: Black Swan: Abductive and Defeasible Video Reasoning in Unpredictable Events", https://doi.org/10.21979/N9/HOAFUL, DR-NTU (Data), V1
BlackSwanSuite is a benchmark for evaluating VLMs’ ability to reason about unexpected events through abductive and defeasible tasks. The tasks either artificially limit the amount of visual information provided to models while questioning them about hidden unexpected events, or p... |
Dec 10, 2025 - Junqi ZHAO
Zhang, Wenyu; Ng, Wei En; Ma, Lixin; Wang, Yuwen; Zhao, Junqi; Koenecke, Allison; Li, Boyang; Wang, Lu, 2025, "Replication Data for: SPHERE: A Hierarchical Evaluation on Spatial Perception and Reasoning for Vision-Language Models", https://doi.org/10.21979/N9/HI9OFD, DR-NTU (Data), V2
SPHERE (Spatial Perception and Hierarchical Evaluation of Reasoning) is a hierarchical evaluation framework built on a new human-annotated dataset of 2,285 question–answer pairs. It systematically probes models across increasing levels of complexity, from fundamental skills to mu... |
