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Found 23 papers, 5 papers with code
A Study on Educational Data Analysis and Personalized Feedback Report Generation Based on Tags and ChatGPT
This study introduces a novel method that employs tag annotation coupled with the ChatGPT language model to analyze student learning behaviors and generate personalized feedback.
POINTS1.5: Building a Vision-Language Model towards Real World Applications
Due to the scarcity of open-source Chinese datasets for vision-language models, we collect numerous images from the Internet and annotate them using a combination of manual and automatic methods.
Non-target Divergence Hypothesis: Toward Understanding Domain Gaps in Cross-Modal Knowledge Distillation
Compared to single-modal knowledge distillation, cross-modal knowledge distillation faces more severe challenges due to domain gaps between modalities.
Towards Realistic Example-based Modeling via 3D Gaussian Stitching
To this end, we present an example-based modeling method that combines multiple Gaussian fields in a point-based representation using sample-guided synthesis.
Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting
Thanks to ASG, we have significantly improved the ability of 3D-GS to model scenes with specular and anisotropic components without increasing the number of 3D Gaussians.
Retrieval-Augmented Generation for Large Language Models: A Survey
Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.
SIRe-IR: Inverse Rendering for BRDF Reconstruction with Shadow and Illumination Removal in High-Illuminance Scenes
Implicit neural representation has opened up new possibilities for inverse rendering.
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning
Recent advancements enlarge the capabilities of large language models (LLMs) in zero-shot image-to-text generation and understanding by integrating multi-modal inputs.
Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction
Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering.
A General Implicit Framework for Fast NeRF Composition and Rendering
Mainly, our work introduces a new surface representation known as Neural Depth Fields (NeDF) that quickly determines the spatial relationship between objects by allowing direct intersection computation between rays and implicit surfaces.
Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities
Multi-Sensor Fusion (MSF) based perception systems have been the foundation in supporting many industrial applications and domains, such as self-driving cars, robotic arms, and unmanned aerial vehicles.
TCBERT: A Technical Report for Chinese Topic Classification BERT
Bidirectional Encoder Representations from Transformers or BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various NLP tasks due to its remarkable performance.
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
We propose a new paradigm for zero-shot learners that is format agnostic, i. e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis.
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
We hope that this project will be the foundation of Chinese cognitive intelligence.
DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks
Moreover, in order to improve the performance of the MO-PPO algorithm, two update strategies, i. e., action-value-based update strategy (AVUS) and loss function-based update strategy (LFUS), are investigated.
Intelligent Trajectory Design for RIS-NOMA aided Multi-robot Communications
The goal is to maximize the sum-rate of whole trajectories for the multi-robot system by jointly optimizing trajectories and NOMA decoding orders of robots, phase-shift coefficients of the RIS, and the power allocation of the AP, subject to predicted initial and final positions of robots and the quality of service (QoS) of each robot.
Coverage and Capacity Optimization in STAR-RISs Assisted Networks: A Machine Learning Approach
Coverage and capacity are the important metrics for performance evaluation in wireless networks, while the coverage and capacity have several conflicting relationships, e. g. high transmit power contributes to large coverage but high inter-cell interference reduces the capacity performance.
Deep-learning-based Hyperspectral imaging through a RGB camera
Hyperspectral image (HSI) contains both spatial pattern and spectral information which has been widely used in food safety, remote sensing, and medical detection.
Improvement of image classification by multiple optical scattering
Multiple optical scattering occurs when light propagates in a non-uniform medium.
Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems
Firstly, we decouple the optimization problem and design the active beamforming for a given IRS configuration.
Revealing Critical Characteristics of Mobility Patterns in New York City during the Onset of COVID-19 Pandemic
Using data sources related to population density, aggregated population mobility, public rail transit use, vehicle use, hotspot and non-hotspot movement patterns, and human activity agglomeration, we analyzed the inter-borough and intra-borough moment for New York City by aggregating the data at the borough level.
Physics and Society Social and Information Networks
Robotic Communications for 5G and Beyond: Challenges and Research Opportunities
Furthermore, dynamic trajectory design and resource allocation for both indoor and outdoor robots are provided to verify the performance of robotic communications in the context of typical robotic application scenarios.
Robotics Systems and Control Signal Processing Systems and Control
Trajectory and Passive Beamforming Design for IRS-aided Multi-Robot NOMA Indoor Networks
A novel intelligent reflecting surface (IRS)-aided multi-robot network is proposed, where multiple mobile wheeled robots are served by an access point (AP) through non-orthogonal multiple access (NOMA).
Robotics
