Search Results for author:
Found 8 papers, 2 papers with code
LLsM: Generative Linguistic Steganography with Large Language Model
Regarding open-source LLMs, we reconstruct the token generator of LLM to the "stego generator" so that it can control the generation of stego based on the secret.
UP4LS: User Profile Constructed by Multiple Attributes for Enhancing Linguistic Steganalysis
In this paper, we propose the UP4LS, a novel framework with the User Profile for enhancing LS performance.
Propagate And Calibrate: Real-time Passive Non-line-of-sight Tracking
In contrast, we propose a purely passive method to track a person walking in an invisible room by only observing a relay wall, which is more in line with real application scenarios, e. g., security.
Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding
We define a maximum traceable distance metric, through which we learn to what extent the text contrastive learning benefits from the historical information of negative samples.
ESOD:Edge-based Task Scheduling for Object Detection
In detail, we train a DNN model (termed as pre-model) to predict which object detection model to use for the coming task and offloads to which edge servers by physical characteristics of the image task (e. g., brightness, saturation).
Improving Adversarial Robustness for Free with Snapshot Ensemble
Based on the snapshot ensemble, we present a new method that is easier to implement: unlike original snapshot ensemble that seeks for local minima, our snapshot ensemble focuses on the last few iterations of a training and stores the sets of parameters from them.
I-Nema: A Biological Image Dataset for Nematode Recognition
In this paper, we identify two main bottlenecks: (1) the lack of a publicly available imaging dataset for diverse species of nematodes (especially the species only found in natural environment) which requires considerable human resources in field work and experts in taxonomy, and (2) the lack of a standard benchmark of state-of-the-art deep learning techniques on this dataset which demands the discipline background in computer science.
Imaging disorder-induced scattering centers in quantum Hall incompressible strip
While the disorder-induced quantum Hall (QH) effect has been studied previously, the effect ofdisorder potential on microscopic features of the integer QH effect remains unclear, particularly forthe incompressible (IC) strip.
Mesoscale and Nanoscale Physics
