metadata
tags:
- text-classification
widget:
- text: >-
This paper presents OASIS, novel one-pass aligned atlas set for image
segmentation. Traditional atlas-based segmentation methods often require
multiple iterations of registration, which can be time-consuming and
computationally expensive. OASIS addresses this limitation by introducing
one-pass alignment process that efficiently registers template atlas to a
target image. This process involves two steps: coarse alignment using a
deep convolutional neural network, followed by a fine alignment using a
robust multiresolution registration algorithm. Experimental results on
various medical imaging datasets demonstrate that OASIS achieves
competitive segmentation accuracy compared to state-of-the-art methods,
while significantly reducing computation time. Additionally, OASIS
exhibits robustness against image artifacts and variations, making it
suitable for wide range of applications in medical imaging and beyond.
Overall, this paper presents a new approach to atlas-based image
segmentation that addresses the limitations of traditional methods, and
offers improved speed, accuracy, and robustness.
example_title: example1
- text: >-
High school graduation is often looked upon as a milestone for students to
celebrate as the end of a long educational journey. However, some school
districts have begun allowing students to graduate a year early. Though
this can be beneficial in certain cases, there are several compelling
reasons why this practice should not be made universally available to all
high school students. Most importantly, graduates who jump the gun and
finish high school early could be missing out on valuable learning
experiences. High school is a formative period and the curriculum is
designed to prepare young adults for college or the workforce. Skipping
ahead by a year could lead to students not having enough guidance or
mentorship available while learning vital skills and life lessons. In
addition, early graduation can leave students feeling unprepared for the
world outside of high school. Not having the same college exposure as
other peers or lacking the maturity that comes with an extra year of
school can hold graduates back from success in the long-run. Graduating a
year earlier than expected does not always mean students will attend
college earlier; in fact, it could mean starting a career ill-equipped to
handle all the responsibilities that come with being a full-time working
adult. For these reasons, schools districts should not make it possible
for all high school students to graduate a year early. The benefits may be
enticing, but there are many potential downsides to consider.
example_title: example2
- text: >-
Summer is a time of hanging out with friends at the beach and relaxing in
the warm weather, but there is always something that swoops in to mess it
up: a summer project. Summer projects are not all bad, for they are
designed to ensure that students continue to learn during their three
month getaway from school. However, who should design the summer project
the student or the teacher? Summer projects should be teacher-designed
because teachers have more experience with projects than students, and
students will lean toward designing a quick and easy project. Teachers
have had more encounters with school assigned projects in their lifetime
than their students. Most teachers have college degrees. They have done
the twelve plus years of primary school to graduate, and then gone on to
college and done two to four more years to get their degree. Through all
that schooling many projects have been assigned and completed. All of this
gives teachers the proper experience and background to come up with a well
designed summer project for their students. Just this past summer my
computer system networking teacher, Mr. Generic_Name, assigned us a
project. It was a review project incorporating all of the course material
from my sophomore year that he did not want us to forget during the
summer. I remember how well rounded of a project it was, so much so that I
had to ask him how he come up with it. Mr. Generic_Name told me that the
project was inspired by all the projects he encountered during his four
years at William and Mary. Due to Mr. Generic_Name having plenty of
experience with higher education projects, it allowed him to design a well
developed summer project for my peers and I. I can only imagine the
toddler like projects that would have been produced if my peers and I were
allowed to design our summer projects instead of Mr. Generic_Name. More
than likely if a student is given the opportunity to do less work they are
going to take that opportunity. Throughout my years of high school I have
seen this exact manner take place over and over. Students will take the
easy way out by selecting courses that have a history of demanding very
little from those enrolled. This same mannerism repeats itself once the
student is enrolled in a course and it comes time to actually work. Just
this past marking period my Math Analysis teacher, Mrs. Generic_Name, gave
us a take home test for winter break. This test consisted of 47 problems.
The more problems you did the higher grade you got, but students did not
seem to take advantage of this. More than half of my class chose to only
do 30 of the 47 problems. This was because completing 30 of the 47
problems earned the minimum for a passing grade, a 70 percent. My peers
had full control of their grades and chose to only work for the minimum
passing score so that the rest of their winter break would be free of
math. This is what will occur if a student is allowed to design their own
summer project. Once a student realizes that they get to design their
project they will make it something simple, lousy, and childlike. The
student will design something just good enough too pass, so that they can
return to their more practical summer. Some argue that a student would be
more inclined to do their project if they got to design it. However, this
is not true as someone's interest in something does not determine whether
they will do it or not, but their work ethic is the true determining
factor. Summer projects serve a meaningful purpose; to make sure kids
maintain learning and strengthening their brains even when school is out.
Something with a strong purpose like that should not be taken lightly and
should be handled by someone who can produce the best project. This is why
summer projects should be teacher-designed, so that students can take away
as much information as possible when the project is all said and done.
example_title: example3
metrics:
- accuracy
- f1
- roc_auc
base_model:
- intfloat/e5-small
library_name: transformers
datasets:
- liamdugan/raid
model-index:
- name: >-
A Shared Benchmark for Robust Evaluation of Machine-Generated Text
Detectors
results:
- task:
type: text-classification
dataset:
name: RAID-test
type: RAID-test
metrics:
- name: accuracy
type: accuracy
value: 0.939
source:
name: RAID Benchmark Leaderboard
url: https://raid-bench.xyz/leaderboard
pipeline_tag: text-classification
My LoRA Fine-Tuned AI-generated Detector
This is a e5-small model fine-tuned with LoRA for sequence classification tasks. It is optimized to classify text into AI-generated or human-written with high accuracy.
- Label_0: Represents human-written content.
- Label_1: Represents AI-generated content.
Model Details
- Base Model:
intfloat/e5-small - Fine-Tuning Technique: LoRA (Low-Rank Adaptation)
- Task: Sequence Classification
- Use Cases: Text classification for AI-generated detection.
- Hyperparameters:
- Learning rate:
5e-5 - Epochs:
3 - LoRA rank:
8 - LoRA alpha:
16
- Learning rate:
Training Details
- Dataset:
- 10,000 twitters and 10,000 rewritten twitters with GPT-4o-mini.
- 80,000 human-written text from RAID-train.
- 128,000 AI-generated text from RAID-train.
- Hardware: Fine-tuned on a single NVIDIA A100 GPU.
- Training Time: Approximately 2 hours.
- Evaluation Metrics:
Metric (Raw) E5-small Fine-tuned Accuracy 65.2% 89.0% F1 Score 0.653 0.887 AUC 0.697 0.976
Collaborators
- Menglin Zhou
- Jiaping Liu
- Xiaotian Zhan
Citation
If you use this model, please cite the RAID dataset as follows:
@inproceedings{dugan-etal-2024-raid,
title = "{RAID}: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors",
author = "Dugan, Liam and
Hwang, Alyssa and
Trhl{\'\i}k, Filip and
Zhu, Andrew and
Ludan, Josh Magnus and
Xu, Hainiu and
Ippolito, Daphne and
Callison-Burch, Chris",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-long.674",
pages = "12463--12492",
}