Search Results for author:
Found 12 papers, 5 papers with code
Sequential-NIAH: A Needle-In-A-Haystack Benchmark for Extracting Sequential Needles from Long Contexts
Evaluating the ability of large language models (LLMs) to handle extended contexts is critical, particularly for retrieving information relevant to specific queries embedded within lengthy inputs.
RmGPT: Rotating Machinery Generative Pretrained Model
Extensive experiments demonstrate that RmGPT significantly outperforms state-of-the-art algorithms, achieving near-perfect accuracy in diagnosis tasks and exceptionally low errors in prognosis tasks.
Exploring the potential of collaborative UAV 3D mapping in Kenyan savanna for wildlife research
UAV-based biodiversity conservation applications have exhibited many data acquisition advantages for researchers.
Topology Optimization of Random Memristors for Input-Aware Dynamic SNN
To address these fundamental challenges, we introduce pruning optimization for input-aware dynamic memristive spiking neural network (PRIME).
Dynamic neural network with memristive CIM and CAM for 2D and 3D vision
In contrast, AI models are static, unable to associate inputs with past experiences, and run on digital computers with physically separated memory and processing.
SfM on-the-fly: Get better 3D from What You Capture
In the last twenty years, Structure from Motion (SfM) has been a constant research hotspot in the fields of photogrammetry, computer vision, robotics etc., whereas real-time performance is just a recent topic of growing interest.
Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver
We experimentally validate our approach by developing a digital twin of the HP memristor, which accurately extrapolates its nonlinear dynamics, achieving a 4. 2-fold projected speedup and a 41. 4-fold projected decrease in energy consumption compared to state-of-the-art digital hardware, while maintaining an acceptable error margin.
Efficient and accurate neural field reconstruction using resistive memory
The GE harnesses the intrinsic stochasticity of resistive memory for efficient input encoding, while the PE achieves precise weight mapping through a Hardware-Aware Quantization (HAQ) circuit.
Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Model
Demonstrating equivalent generative quality to the software baseline, our system achieved remarkable enhancements in generative speed for both unconditional and conditional generation tasks, by factors of 64. 8 and 156. 5, respectively.
Random resistive memory-based deep extreme point learning machine for unified visual processing
Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks.
On-the-Fly SfM: What you capture is What you get
Over the last decades, ample achievements have been made on Structure from motion (SfM).
BERTSel: Answer Selection with Pre-trained Models
we are the first to explore the performance of fine-tuning BERT for answer selection.
