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Found 12 papers, 2 papers with code
Rephrase and Contrast: Fine-Tuning Language Models for Enhanced Understanding of Communication and Computer Networks
Large language models (LLMs) are being widely researched across various disciplines, with significant recent efforts focusing on adapting LLMs for understanding of how communication networks operate.
Addressing Out-of-Distribution Challenges in Image Semantic Communication Systems with Multi-modal Large Language Models
Semantic communication is a promising technology for next-generation wireless networks.
LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic Surgery
We further design an adaptive weight assignment approach that balances the generalization ability of the LLM and the domain expertise of the old CL model.
An Autonomous Large Language Model Agent for Chemical Literature Data Mining
The proposed approach marks a significant advancement in automating chemical literature extraction and demonstrates the potential for AI to revolutionize data management and utilization in chemistry.
LLMind: Orchestrating AI and IoT with LLM for Complex Task Execution
Task-oriented communications are an important element in future intelligent IoT systems.
Chemist-X: Large Language Model-empowered Agent for Reaction Condition Recommendation in Chemical Synthesis
Recent AI research plots a promising future of automatic chemical reactions within the chemistry society.
Nonlinear Multi-Carrier System with Signal Clipping: Measurement, Analysis, and Optimization
With the derivations, we investigate the optimal system setting to achieve the SER lower bound in a practical OFDM system that considers both PA nonlinearity and clipping distortion.
The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms
We begin by exploring LLM-assisted code refactoring, reuse, and validation, using an open-source software-defined radio (SDR) project as a case study.
AMD-DBSCAN: An Adaptive Multi-density DBSCAN for datasets of extremely variable density
DBSCAN has been widely used in density-based clustering algorithms.
Consistency of Implicit and Explicit Features Matters for Monocular 3D Object Detection
This paper studies 3D intermediate representation methods which generate intermediate 3D features for subsequent tasks.
Ranked #1 on
Monocular 3D Object Detection
on KITTI Cars Moderate
(using extra training data)
Efficient FFT Computation in IFDMA Transceivers
Our experimental results indicate that when the number of hardware processors is a power of two: 1) MPS-FFT has near-optimal computation time; 2) MPS-FFT incurs less than 44. 13\% of the computation time of the conventional pipelined FFT.
Flow Sampling: Network Monitoring in Large-Scale Software-Defined IoT Networks
Software-defined Internet-of-Things networking (SDIoT) greatly simplifies the network monitoring in large-scale IoT networks by per-flow sampling, wherein the controller keeps track of all the active flows in the network and samples the IoT devices on each flow path to collect real-time flow statistics.
