Search Results for author:
Found 17 papers, 3 papers with code
CodeVision: Detecting LLM-Generated Code Using 2D Token Probability Maps and Vision Models
The rise of large language models (LLMs) like ChatGPT has significantly improved automated code generation, enhancing software development efficiency.
Logic Error Localization in Student Programming Assignments Using Pseudocode and Graph Neural Networks
Additionally, we have devised a method to efficiently gather logic-error-prone programs during the syntax error correction process and compile these into a dataset that includes single and multiple line logic errors, complete with indices of the erroneous lines.
LecPrompt: A Prompt-based Approach for Logical Error Correction with CodeBERT
In this paper, we introduce LecPrompt to localize and repair logical errors, an prompt-based approach that harnesses the capabilities of CodeBERT, a transformer-based large language model trained on code.
FreqMark: Frequency-Based Watermark for Sentence-Level Detection of LLM-Generated Text
The increasing use of Large Language Models (LLMs) for generating highly coherent and contextually relevant text introduces new risks, including misuse for unethical purposes such as disinformation or academic dishonesty.
Signal Watermark on Large Language Models
As Large Language Models (LLMs) become increasingly sophisticated, they raise significant security concerns, including the creation of fake news and academic misuse.
Multi-Task Program Error Repair and Explanatory Diagnosis
And program error diagnosis can often be too abstract or technical for developers to understand, especially for beginners.
Neuromorphic spatiotemporal optical flow: Enabling ultrafast visual perception beyond human capabilities
Optical flow, inspired by the mechanisms of biological visual systems, calculates spatial motion vectors within visual scenes that are necessary for enabling robotics to excel in complex and dynamic working environments.
A New Method in Facial Registration in Clinics Based on Structure Light Images
To abundant traditional image methods with depth information, a method in registering with depth images and traditional clinical images was investigated.
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.
A High-Performance, Reconfigurable, Fully Integrated Time-Domain Reflectometry Architecture Using Digital I/Os
These results demonstrate that a fully reconfigurable and highly integrated TDR (iTDR) can be implemented on a field-programmable gate array (FPGA) chip without using any external circuit components.
PHI-MVS: Plane Hypothesis Inference Multi-view Stereo for Large-Scale Scene Reconstruction
Besides, a new acceleration scheme similar to dilated convolution can speed up the depth map estimating process with only a slight influence on the reconstruction.
Learning Structral coherence Via Generative Adversarial Network for Single Image Super-Resolution
Among the major remaining challenges for single image super resolution (SISR) is the capacity to recover coherent images with global shapes and local details conforming to human vision system.
Gaussian Fusion: Accurate 3D Reconstruction via Geometry-Guided Displacement Interpolation
Reconstructing delicate geometric details with consumer RGB-D sensors is challenging due to sensor depth and poses uncertainties.
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020.
MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction
The ambiguity in image matching is one of main factors decreasing the quality of the 3D model reconstructed by PatchMatch based multiple view stereo.
Challenge report: Recognizing Families In the Wild Data Challenge
In this paper, we studied previous methods and proposed our method.
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.
