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Found 39 papers, 11 papers with code
When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time?
The weighted low-rank approximation problem is a fundamental numerical linear algebra problem and has many applications in machine learning.
Rethinking Tokenized Graph Transformers for Node Classification
In this paper, we observe that the generations of token sequences in existing GTs only focus on the first-order neighbors on the constructed similarity graphs, which leads to the limited usage of nodes to generate diverse token sequences, further restricting the potential of tokenized GTs for node classification.
Fusion of Millimeter-wave Radar and Pulse Oximeter Data for Low-burden Diagnosis of Obstructive Sleep Apnea-Hypopnea Syndrome
Objective: The aim of the study is to develop a novel method for improved diagnosis of obstructive sleep apnea-hypopnea syndrome (OSAHS) in clinical or home settings, with the focus on achieving diagnostic performance comparable to the gold-standard polysomnography (PSG) with significantly reduced monitoring burden.
MapExpert: Online HD Map Construction with Simple and Efficient Sparse Map Element Expert
Existing solutions typically attempt to detect vectorized HD map elements with unified models; however, these methods often overlook the distinct characteristics of different non-cubic map elements, making accurate distinction challenging.
Efficacy of Temporal Interference Electrical Stimulation for Spinal Cord Injury Rehabilitation: A Case Series
This study explores the efficacy of TI stimulation as a non-invasive approach for improving motor and sensory function in patients with incomplete SCI.
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
Our key contributions are prompt tuning on \textit{single-head} transformers with only a \textit{single} self-attention layer: (i) is universal, and (ii) supports efficient (even almost-linear time) algorithms under the Strong Exponential Time Hypothesis (SETH).
GLDesigner: Leveraging Multi-Modal LLMs as Designer for Enhanced Aesthetic Text Glyph Layouts
Text logo design heavily relies on the creativity and expertise of professional designers, in which arranging element layouts is one of the most important procedures.
Detection of Sleep Apnea-Hypopnea Events Using Millimeter-wave Radar and Pulse Oximeter
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a sleep-related breathing disorder associated with significant morbidity and mortality worldwide.
Deep Computer Vision for Solar Physics Big Data: Opportunities and Challenges
With recent missions such as advanced space-based observatories like the Solar Dynamics Observatory (SDO) and Parker Solar Probe, and ground-based telescopes like the Daniel K. Inouye Solar Telescope (DKIST), the volume, velocity, and variety of data have made solar physics enter a transformative era as solar physics big data (SPBD).
Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method
Leverage scores have become essential in statistics and machine learning, aiding regression analysis, randomized matrix computations, and various other tasks.
Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks
In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets.
MetaDesigner: Advancing Artistic Typography Through AI-Driven, User-Centric, and Multilingual WordArt Synthesis
MetaDesigner introduces a transformative framework for artistic typography synthesis, powered by Large Language Models (LLMs) and grounded in a user-centric design paradigm.
Class-Aware Cartilage Segmentation for Autonomous US-CT Registration in Robotic Intercostal Ultrasound Imaging
Then, a dense skeleton graph-based non-rigid registration is presented to map the intercostal scanning path from a generic template to individual patients.
A Transformer variant for multi-step forecasting of water level and hydrometeorological sensitivity analysis based on explainable artificial intelligence technology
The variant model is utilized for multi-step forecasting of water level, by considering meteorological and hydrological factors simultaneously.
Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond
The softmax activation function plays a crucial role in the success of large language models (LLMs), particularly in the self-attention mechanism of the widely adopted Transformer architecture.
Exploring Dynamic Transformer for Efficient Object Tracking
For instance, DyTrack obtains 64. 9% AUC on LaSOT with a speed of 256 fps.
VibNet: Vibration-Boosted Needle Detection in Ultrasound Images
The results obtained on porcine samples demonstrate that VibNet effectively detects needles even when their visibility is severely reduced, with a tip error of $1. 61\pm1. 56~mm$ compared to $8. 15\pm9. 98~mm$ for UNet and $6. 63\pm7. 58~mm$ for WNet, and a needle direction error of $1. 64\pm1. 86^{\circ}$ compared to $9. 29\pm15. 30^{\circ}$ for UNet and $8. 54\pm17. 92^{\circ}$ for WNet.
DyRoNet: Dynamic Routing and Low-Rank Adapters for Autonomous Driving Streaming Perception
The advancement of autonomous driving systems hinges on the ability to achieve low-latency and high-accuracy perception.
Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs
We direct our focus to the complex algebraic learning task of modular addition involving $k$ inputs.
WordArt Designer API: User-Driven Artistic Typography Synthesis with Large Language Models on ModelScope
This paper introduces the WordArt Designer API, a novel framework for user-driven artistic typography synthesis utilizing Large Language Models (LLMs) on ModelScope.
Tracking with Human-Intent Reasoning
The perception component then generates the tracking results based on the embeddings.
Ranked #5 on
Referring Video Object Segmentation
on ReVOS
One Pass Streaming Algorithm for Super Long Token Attention Approximation in Sublinear Space
Considering a single-layer self-attention with Query, Key, and Value matrices $Q, K, V \in \mathbb{R}^{n \times d}$, the polynomial method approximates the attention output $T \in \mathbb{R}^{n \times d}$.
A Theoretical Insight into Attack and Defense of Gradient Leakage in Transformer
The Deep Leakage from Gradient (DLG) attack has emerged as a prevalent and highly effective method for extracting sensitive training data by inspecting exchanged gradients.
WordArt Designer: User-Driven Artistic Typography Synthesis using Large Language Models
This paper introduces WordArt Designer, a user-driven framework for artistic typography synthesis, relying on the Large Language Model (LLM).
Implementing a new fully stepwise decomposition-based sampling technique for the hybrid water level forecasting model in real-world application
Results of VMD-based hybrid model using FSDB sampling technique show that Nash-Sutcliffe Efficiency (NSE) coefficient is increased by 6. 4%, 28. 8% and 7. 0% in three stations respectively, compared with those obtained from the currently most advanced sampling technique.
Real-time frequency measurement based on parallel pipeline FFT for time-stretched acquisition system
Real-time frequency measurement for non-repetitive and statistically rare signals are challenging problems in the electronic measurement area, which places high demands on the bandwidth, sampling rate, data processing and transmission capabilities of the measurement system.
Tracking Anything in High Quality
To further improve the quality of tracking masks, a pretrained MR model is employed to refine the tracking results.
Ranked #5 on
Semi-Supervised Video Object Segmentation
on YouTube-VOS 2019
(using extra training data)
Thoracic Cartilage Ultrasound-CT Registration using Dense Skeleton Graph
To address this challenge, a graph-based non-rigid registration is proposed to enable transferring planned paths from the atlas to the current setup by explicitly considering subcutaneous bone surface features instead of the skin surface.
KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration
By spearheading the integration of Multilateration with facial analysis, KeyPosS marks a paradigm shift in facial landmark detection.
DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving
Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that has yet to be thoroughly explored in existing research.
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence Guarantee
This paper focuses on two model compression techniques: low-rank approximation and weight pruning in neural networks, which are very popular nowadays.
ProContEXT: Exploring Progressive Context Transformer for Tracking
Existing Visual Object Tracking (VOT) only takes the target area in the first frame as a template.
Ranked #1 on
Video Object Tracking
on NT-VOT211
LongShortNet: Exploring Temporal and Semantic Features Fusion in Streaming Perception
Streaming perception is a critical task in autonomous driving that requires balancing the latency and accuracy of the autopilot system.
Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks
After this, we use the Siamese-based network to compute the similarity of the generation image patch and original image patch.
Improving Zero-shot Multilingual Neural Machine Translation for Low-Resource Languages
Although the multilingual Neural Machine Translation(NMT), which extends Google's multilingual NMT, has ability to perform zero-shot translation and the iterative self-learning algorithm can improve the quality of zero-shot translation, it confronts with two problems: the multilingual NMT model is prone to generate wrong target language when implementing zero-shot translation; the self-learning algorithm, which uses beam search to generate synthetic parallel data, demolishes the diversity of the generated source language and amplifies the impact of the same noise during the iterative learning process.
Pretrain-Finetune Based Training of Task-Oriented Dialogue Systems in a Real-World Setting
In this work, we present a method for training retrieval-based dialogue systems using a small amount of high-quality, annotated data and a larger, unlabeled dataset.
Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs
The two-level alignment acts as two different constraints on different relations of the shared entities and facilitates better knowledge transfer for relational learning on multiple bipartite graphs.
Dual Graph Embedding for Object-Tag LinkPrediction on the Knowledge Graph
Most existing methods focus on preserving the first-order proximity between entities in the KG.
Skeleton-based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Module
In this paper, we first leverage a robust feature descriptor, path signature (PS), and propose three PS features to explicitly represent the spatial and temporal motion characteristics, i. e., spatial PS (S_PS), temporal PS (T_PS) and temporal spatial PS (T_S_PS).
Ranked #1 on
Gesture Recognition
on ChaLearn 2013
