Search Results for author:
Found 21 papers, 8 papers with code
MMEKG: Multi-modal Event Knowledge Graph towards Universal Representation across Modalities
Events are fundamental building blocks of real-world happenings.
Semi-Automatic Line-System Provisioning with Integrated Physical-Parameter-Aware Methodology: Field Verification and Operational Feasibility
We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario.
FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs
However, existing GPU and transformer-based accelerators cannot efficiently process compressed LLMs, due to the following unresolved challenges: low computational efficiency, underutilized memory bandwidth, and large compilation overheads.
TeTriRF: Temporal Tri-Plane Radiance Fields for Efficient Free-Viewpoint Video
Neural Radiance Fields (NeRF) revolutionize the realm of visual media by providing photorealistic Free-Viewpoint Video (FVV) experiences, offering viewers unparalleled immersion and interactivity.
K-BMPC: Derivative-based Koopman Bilinear Model Predictive Control For Tractor-trailer Trajectory Tracking With Unknown Parameters
Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem.
DualAug: Exploiting Additional Heavy Augmentation with OOD Data Rejection
Most existing data augmentation methods tend to find a compromise in augmenting the data, \textit{i. e.}, increasing the amplitude of augmentation carefully to avoid degrading some data too much and doing harm to the model performance.
Fast WDM provisioning with minimal probing: the first field experiments for DC exchanges
Then, using field fibers deployed in the NSF COSMOS testbed (deployed in an urban area), a Linux-based transmission device software architecture, and coherent transceivers with different optical frequency ranges, modulators, and modulation formats, the fast WDM provisioning of an optical path was completed within 6 minutes (with a Q-factor error of about 0. 7 dB).
Self-Normalizing Neural Network, Enabling One Shot Transfer Learning for Modeling EDFA Wavelength Dependent Gain
We present a novel ML framework for modeling the wavelength-dependent gain of multiple EDFAs, based on semi-supervised, self-normalizing neural networks, enabling one-shot transfer learning.
Few-shot Event Detection: An Empirical Study and a Unified View
Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e. g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress. This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline.
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding
By aligning the classes of previous datasets to our semantic space, we gather (image/video/skeleton/MoCap) datasets into a unified database in a unified label system, i. e., bridging "isolated islands" into a "Pangea".
Sepformer-based Models: More Efficient Models for Long Sequence Time-Series Forecasting
These include: 1) complexity - Informer has a relatively high computational complexity and a high memory overhead; 2) nuance - there is limited ability to capture the subtle features in a data stream; 3) interpretability - the inference procedure of Informer is not explainable; 4) extensibility - accuracy is poor with extra-long multivariate time series.
Layout-aware Dreamer for Embodied Referring Expression Grounding
In this work, we study the problem of Embodied Referring Expression Grounding, where an agent needs to navigate in a previously unseen environment and localize a remote object described by a concise high-level natural language instruction.
A robust feature reinforcement framework for heterogeneous graphs neural networks
Heterogeneous graph embedding is a crucial step in HGNNs.
Find a Way Forward: a Language-Guided Semantic Map Navigator
In this paper, we introduce the map-language navigation task where an agent executes natural language instructions and moves to the target position based only on a given 3D semantic map.
Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction
We have conducted extensive experiments on three benchmarks, including both sentence- and document-level EAE.
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
We introduce two alternatives for sparse adversarial training: (i) static sparsity, by leveraging recent results from the lottery ticket hypothesis to identify critical sparse subnetworks arising from the early training; (ii) dynamic sparsity, by allowing the sparse subnetwork to adaptively adjust its connectivity pattern (while sticking to the same sparsity ratio) throughout training.
A frequency domain analysis of gradient-based adversarial examples
And the log-spectrum difference of the adversarial examples and clean image is more concentrated in the high-frequency part than the low-frequency part.
Exploring Inherent Properties of the Monophonic Melody of Songs
Unlike other components in music theory, such as harmony and counterpoint, computable features for melody is urgently in need.
Information Compensation for Deep Conditional Generative Networks
In recent years, unsupervised/weakly-supervised conditional generative adversarial networks (GANs) have achieved many successes on the task of modeling and generating data.
Musical Instrument Playing Technique Detection Based on FCN: Using Chinese Bowed-Stringed Instrument as an Example
The effectiveness of the proposed framework is tested on a new dataset, its categorization of techniques is similar to our training dataset.
