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Found 34 papers, 11 papers with code
When LLM-based Code Generation Meets the Software Development Process
Results indicate LCGScrum outperforms other models, achieving Pass@1 scores of 75. 2, 65. 5, 82. 5, and 56. 7 in HumanEval, HumanEval-ET, MBPP, and MBPP-ET, respectively - an average 15% improvement over GPT.
Ranked #6 on
Code Generation
on MBPP
Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection
In this paper, we try to tackle these challenges through three designs: (1) We present a novel framework to capture broader forgery clues by extracting multiple non-overlapping local representations and fusing them into a global semantic-rich feature.
CLIPose: Category-Level Object Pose Estimation with Pre-trained Vision-Language Knowledge
Inspired by this motivation, we propose CLIPose, a novel 6D pose framework that employs the pre-trained vision-language model to develop better learning of object category information, which can fully leverage abundant semantic knowledge in image and text modalities.
Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-Correct Decoding
This research aims to accelerate the inference speed of large language models (LLMs) with billions of parameters.
BiTA: Bi-Directional Tuning for Lossless Acceleration in Large Language Models
Large language models (LLMs) commonly employ autoregressive generation during inference, leading to high memory bandwidth demand and consequently extended latency.
ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach
However, despite their promising efficiency, almost all existing machine unlearning methods handle unlearning requests independently from inference requests, which unfortunately introduces a new security issue of inference service obsolescence and a privacy vulnerability of undesirable exposure for machine unlearning in MLaaS.
FLTracer: Accurate Poisoning Attack Provenance in Federated Learning
In this paper, we first conduct a comprehensive study on prior FL attacks and detection methods.
SoybeanNet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (UAV) Images
Soybeans are a critical source of food, protein and oil, and thus have received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques.
Coordination Control of Discrete Event Systems under Cyber Attacks
This paper investigates the coordination control of discrete event systems in the presence of combined sensor and actuator attacks.
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Deepfake has taken the world by storm, triggering a trust crisis.
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
However, the accuracy of detection models degrades significantly on images generated by new deepfake methods due to the difference in data distribution.
Learning in Dynamic Systems and Its Application to Adaptive PID Control
In order to introduce self-learning to dynamic systems other than neural networks, we extend the Brandt-Lin learning algorithm of neural networks to a large class of dynamic systems.
Active Fault Isolation for Discrete Event Systems
The method of combining two control mechanisms can be used to synthesize more powerful supervisors for other supervisory control problems of discrete event systems as well.
Universal Object Detection with Large Vision Model
In this study, our focus is on a specific challenge: the large-scale, multi-domain universal object detection problem, which contributes to the broader goal of achieving a universal vision system.
Intelligent Computing: The Latest Advances, Challenges and Future
In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications.
Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples
In this paper, we propose a voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services.
Modeling and Control of Discrete Event Systems under Joint Sensor-Actuator Cyber Attacks
We define the upper-bound on all possible languages that can be generated by the supervised system to investigate the safety supervisory control problem under cyber attacks.
Convergence of a New Learning Algorithm
A new learning algorithm proposed by Brandt and Lin for neural network [1], [2] has been shown to be mathematically equivalent to the conventional back-propagation learning algorithm, but has several advantages over the backpropagation algorithm, including feedback-network-free implementation and biological plausibility.
Hybrid 3D Beamforming Relying on Sensor-Based Training and Channel Estimation for Reconfigurable Intelligent Surface Aided TeraHertz MIMO systems
Moreover, the conditions of maintaining the orthogonality of the RIS-aided THz channel are derived in support of spatial multiplexing.
Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition
Inspired by the recently proposed hierarchy representation of fine-grained actions in FineGym and SlowFast network for action recognition, we propose a novel multi-task network which exploits the FineGym hierarchy representation to achieve effective joint learning and prediction for fine-grained human action recognition.
Stochastic Alternating Direction Method of Multipliers for Byzantine-Robust Distributed Learning
This paper aims to solve a distributed learning problem under Byzantine attacks.
Incorporating VAD into ASR System by Multi-task Learning
When we use End-to-end automatic speech recognition (E2E-ASR) system for real-world applications, a voice activity detection (VAD) system is usually needed to improve the performance and to reduce the computational cost by discarding non-speech parts in the audio.
FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling
This work presents FG-Net, a general deep learning framework for large-scale point clouds understanding without voxelizations, which achieves accurate and real-time performance with a single NVIDIA GTX 1080 GPU.
Ranked #1 on
Semantic Segmentation
on Semantic3D
Injecting Reliable Radio Frequency Fingerprints Using Metasurface for The Internet of Things
Our proposed solution, Metasurface RF-Fingerprinting Injection (MeRFFI), is to inject a carefully-designed radio frequency fingerprint into the wireless physical layer that can increase the security of a stationary IoT device with minimal overhead.
Recognizing Chinese Judicial Named Entity using BiLSTM-CRF
Named entity recognition (NER) plays an essential role in natural language processing systems.
Adversary Helps: Gradient-based Device-Free Domain-Independent Gesture Recognition
Wireless signal-based gesture recognition has promoted the developments of VR game, smart home, etc.
AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups
For this reason, we should use the geodesic to characterize how an image transform along the manifold of a transformation group, and adopt its length to measure the deviation between transformations.
WiPIN: Operation-free Passive Person Identification Using Wi-Fi Signals
Wi-Fi signals-based person identification attracts increasing attention in the booming Internet-of-Things era mainly due to its pervasiveness and passiveness.
Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion
Driven by applications like Micro Aerial Vehicles (MAVs), driver-less cars, etc, localization solution has become an active research topic in the past decade.
Robotics
Disturbance Grassmann Kernels for Subspace-Based Learning
In this paper, we focus on subspace-based learning problems, where data elements are linear subspaces instead of vectors.
Google Map Aided Visual Navigation for UAVs in GPS-denied Environment
We propose a framework for Google Map aided UAV navigation in GPS-denied environment.
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
Given the potential X-ray radiation risk to the patient, low-dose CT has attracted a considerable interest in the medical imaging field.
Real-Time Optical flow-based Video Stabilization for Unmanned Aerial Vehicles
This paper describes the development of a novel algorithm to tackle the problem of real-time video stabilization for unmanned aerial vehicles (UAVs).
Human Gender Classification: A Review
Gender contains a wide range of information regarding to the characteristics difference between male and female.
