Search Results for author:
Found 32 papers, 12 papers with code
Reducing Distributional Uncertainty by Mutual Information Maximisation and Transferable Feature Learning
Distributional uncertainty exists broadly in many real-world applications, one of which in the form of domain discrepancy.
Composition-based Heterogeneous Graph Multi-channel Attention Network for Multi-aspect Multi-sentiment Classification
Aspect-based sentiment analysis (ABSA) has drawn more and more attention because of its extensive applications.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
FaVChat: Unlocking Fine-Grained Facail Video Understanding with Multimodal Large Language Models
To effectively capture rich facial clues, we propose a hybrid model architecture composed of a general visual encoder, a dedicated facial encoder, and a mixture-of-experts-enhanced adapter for adaptive fusion of multi-source visual features.
A Novel Trustworthy Video Summarization Algorithm Through a Mixture of LoRA Experts
With the exponential growth of user-generated content on video-sharing platforms, the challenge of facilitating efficient searching and browsing of videos has garnered significant attention.
AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
Yet, applying generative AI techniques to accelerate the design of analog ICs remains a significant challenge due to critical domain-specific issues, such as the lack of a comprehensive dataset and effective representation methods for analog circuits.
4D SlingBAG: spatial-temporal coupled Gaussian ball for large-scale dynamic 3D photoacoustic iterative reconstruction
However, for existing IR algorithms, multi-frame 3D reconstruction leads to extremely high memory consumption and prolonged computation time, with limited consideration of the spatial-temporal continuity between data frames.
Enhancing elusive clues in knowledge learning by contrasting attention of language models
Causal language models acquire vast amount of knowledge from general text corpus during pretraining, but the efficiency of knowledge learning is known to be unsatisfactory, especially when learning from knowledge-dense and small-sized corpora.
What Do You Want? User-centric Prompt Generation for Text-to-image Synthesis via Multi-turn Guidance
To achieve this, we mined 15 essential dimensions for high-quality prompts from advanced users and curated a multi-turn dataset.
reCSE: Portable Reshaping Features for Sentence Embedding in Self-supervised Contrastive Learning
We propose reCSE, a self supervised contrastive learning sentence representation framework based on feature reshaping.
Sliding Gaussian ball adaptive growth (SlingBAG): point cloud-based iterative algorithm for large-scale 3D photoacoustic imaging
Large-scale 3D photoacoustic (PA) imaging has become increasingly important for both clinical and pre-clinical applications.
Making Task-Oriented Dialogue Datasets More Natural by Synthetically Generating Indirect User Requests
Indirect User Requests (IURs), such as "It's cold in here" instead of "Could you please increase the temperature?"
Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge
The online validation set incorporated 52 HRCT scans from patients with fibrotic lung disease and the offline test set included 140 cases from fibrosis and COVID-19 patients.
Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing
In this paper, we present a novel differentiable point-based rendering framework to achieve photo-realistic relighting.
An Intelligent Social Learning-based Optimization Strategy for Black-box Robotic Control with Reinforcement Learning
Individuals in the learning style use the Levy flight search strategy to learn from the best performer and form the closest relationships.
Human Transcription Quality Improvement
We collect and release LibriCrowd - a large-scale crowdsourced dataset of audio transcriptions on 100 hours of English speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Human-AI Interactions and Societal Pitfalls
When working with generative artificial intelligence (AI), users may see productivity gains, but the AI-generated content may not match their preferences exactly.
HTEC: Human Transcription Error Correction
Therefore, we propose HTEC for Human Transcription Error Correction.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Distributed UAV Swarm Augmented Wideband Spectrum Sensing Using Nyquist Folding Receiver
Further, the block sparse recovery property is analyzed for wide bandwidth signals.
Wideband Power Spectrum Sensing: a Fast Practical Solution for Nyquist Folding Receiver
To address the high-speed sampling bottleneck of wideband spectrum sensing, a fast and practical solution of power spectrum estimation for Nyquist folding receiver (NYFR) is proposed in this paper.
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNN
Convolutional Neural Network (CNN) and Transformer are deep learning-based approaches for network traffic classification.
Quantifying the Benefit of Artificial Intelligence for Scientific Research
The ongoing artificial intelligence (AI) revolution has the potential to change almost every line of work.
Limit Cycles Analysis and Control of Evolutionary Game Dynamics with Environmental Feedback
Recently, an evolutionary game dynamics model taking into account the environmental feedback has been proposed to describe the co-evolution of strategic actions of a population of individuals and the state of the surrounding environment; correspondingly a range of interesting dynamic behaviors have been reported.
Economic MPC-based planning for marine vehicles: Tuning safety and energy efficiency
Energy efficiency and safety are two critical objectives for marine vehicles operating in environments with obstacles, and they generally conflict with each other.
Rational Polynomial Camera Model Warping for Deep Learning Based Satellite Multi-View Stereo Matching
Based on the RPC warping, we propose the deep learning based satellite MVS (SatMVS) framework for large-scale and wide depth range Earth surface reconstruction.
Evolved Massive Stars at Low-metallicity IV. Using 1.6 $μ$m "H-bump" to identify red supergiant stars: a case study of NGC 6822
Further separating RSG candidates from the rest of the LSG candidates is done by using semi-empirical criteria on NIR CMDs and resulted in 323 RSG candidates.
Solar and Stellar Astrophysics Astrophysics of Galaxies
Unsupervised Change Detection in Satellite Images with Generative Adversarial Network
Detecting changed regions in paired satellite images plays a key role in many remote sensing applications.
An anomaly prediction framework for financial IT systems using hybrid machine learning methods
To improve the efficiency and accuracy of system failure detection and thereby reduce the impact of system failures on financial services, we propose a novel machine learning-based framework to predict the occurrence of system exceptions and failures in a financial software system.
Computational Socioeconomics
Uncovering the structure of socioeconomic systems and timely estimation of socioeconomic status are significant for economic development.
The Period-Luminosity Relations of Red Supergiants in M33 and M31
The period-luminosity (P-L) relation is analyzed for the RSGs in the fundamental mode.
Solar and Stellar Astrophysics Astrophysics of Galaxies
Nonparallel Emotional Speech Conversion
Emotion conversion is performed by extracting and recombining the content code of the source speech and the style code of the target emotion.
Diversified Top-k Partial MaxSAT Solving
We introduce a diversified top-k partial MaxSAT problem, a combination of partial MaxSAT problem and enumeration problem.
