Search Results for author:
Found 6 papers, 2 papers with code
LLM-Detector: Improving AI-Generated Chinese Text Detection with Open-Source LLM Instruction Tuning
We then proposed LLM-Detector, a novel method for both document-level and sentence-level text detection through Instruction Tuning of LLMs.
Aurora:Activating Chinese chat capability for Mixtral-8x7B sparse Mixture-of-Experts through Instruction-Tuning
This work is pioneering in the execution of instruction fine-tuning on a sparse expert-mixed model, marking a significant breakthrough in enhancing the capabilities of this model architecture.
Discrepancy-based Active Learning for Weakly Supervised Bleeding Segmentation in Wireless Capsule Endoscopy Images
Specifically, to liberate labor, we design a novel discrepancy decoder model and a CAMPUS (CAM, Pseudo-label and groUnd-truth Selection) criterion to replace the noisy CAMs with accurate model predictions and a few human labels.
Mobile Robots Exploration via Deep Reinforcement Learning
n this paper, we try to solve the mobile robot exploration problem in a 2D indoor office environment by deep reinforcement learning.
Using DP Towards A Shortest Path Problem-Related Application
We apply the designed model and proposed an algorithm for detecting lanes by formulating it as the shortest path problem.
Multiple Lane Detection Algorithm Based on Optimised Dense Disparity Map Estimation
Lane detection is very important for self-driving vehicles.
