Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This repository introduces MentaLLaMA, the first open-source instruction following large language model for interpretable mental health analysis.
| Date | Stars |
|---|---|
| 2026-07-31 | 323 |
| 2026-08-06 | 323 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<p align="center" width="100%">
<img src="https://i.postimg.cc/0Nd8VxbL/logo.png" width="100%" height="100%">
</p>
<div>
<div align="left">
<a href='https://stevekgyang.github.io/' target='_blank'>Kailai Yang<sup>1,2</sup> 
<a href='https://www.zhangtianlin.top/' target='_blank'>Tianlin Zhang<sup>1,2</sup> 
<a target='_blank'>Shaoxiong Ji<sup>3</sup></a> 
<a target='_blank'>Qianqian Xie<sup>1,2</sup></a> 
<a target='_blank'>Ziyan Kuang<sup>6</sup></a> 
<a href='https://research.manchester.ac.uk/en/persons/sophia.ananiadou' target='_blank'>Sophia Ananiadou<sup>1,2,4</sup></a> 
<a target='_blank'>Jimin Huang<sup>5</sup></a>
</div>
<div>
<div align="left">
<sup>1</sup>National Centre for Text Mining 
<sup>2</sup>The University of Manchester 
<sup>3</sup>University of Helsinki 
<sup>4</sup>Artificial Intelligence Research Center, AIST 
<sup>5</sup>Wuhan University 
<sup>6</sup>Jiangxi Normal University 
</div>
<div align="left">
<img src='https://i.postimg.cc/Kj7RzvNr/nactem-hires.png' alt='NaCTeM' height='85px'> 
<img src='https://i.postimg.cc/nc2Jy6FN/uom.png' alt='UoM University Logo' height='85px'> 
<img src='https://i.postimg.cc/cJD3HsRY/helsinki.jpg' alt='helsinki Logo' height='85px'> 
<img src='https://i.postimg.cc/SNpxVKwg/airc-logo.png' alt='airc Logo' height='85px'> 
<img src='https://i.postimg.cc/CLtkBwz7/57-EDDD9-FB0-DF712-F3-AB627163-C2-1-EF15655-13-FCA.png' alt='Wuhan University Logo' height='85px'>
</div>
## News
📢 *Mar. 2, 2024* Full release of the test data for the IMHI benchmark.
📢 *Feb. 1, 2024* Our MentaLLaMA paper:
"MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models" has been accepted
by WWW 2024!
📢 *Oct. 31, 2023* We release the MentaLLaMA-33B-lora model, a 33B edition of MentaLLaMA based on
Vicuna-33B and the full IMHI dataset, but trained with LoRA due to the computational resources!
📢 *Oct. 13, 2023* We release the training data for the following datasets: DR, dreaddit, SAD,
MultiWD, and IRF. More to come, stay tuned!
📢 *Oct. 7, 2023* Our evaluation paper:
"Towards Interpretable Mental Health Analysis with Large Language Models" has been accepted
by EMNLP 2023 main conference as a long paper!
## Ethical Considerations
This repository and its contents are provided for **non-clinical research only**
. None of the material constitutes actual diagnosis or advice, and help-seeker should get assistance
from professional psychiatrists or clinical practitioners. No warranties, express or implied, are offered regarding the accuracy
, completeness, or utility of the predictions and explanations. The authors and contributors are not
responsible for any errors, omissions, or any consequences arising from the use
of the information herein. Users should exercise their own judgment and consult
professionals before making any clinical-related decisions. The use
of the software and information contained in this repository is entirely at the
user's own risk.
The raw datasets collected to build our IMHI dataset are from public
social media platforms such as Reddit and Twitter, and we strictly
follow the privacy protocols and ethical principles to protect
user privacy and guarantee that anonymity is properly applied in
all the mental health-related texts. In addition, to minimize misuse,
all examples provided in our paper are paraphrased and obfuscated
utilizing the moderate disguising scheme.
In addition, recent studies have indicated LLMs may introduce some potential
bias, such as gender gaps. Meanwhile, some incorrect prediction results, inappropriate explanations, and over-generalization
also illustrate the potential risks of current LLMs. Therefore, there
are still many challenges in applying the model to real-scenario
mental health monitoringExcerpt of 23,667 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:14b108a150c5bd77, topic:large-language-models, topic:language-model
matched fp:14b108a150c5bd77, topic:natural-language-processing
matched fp:14b108a150c5bd77, topic:chatgpt
matched fp:14b108a150c5bd77, topic:interpretability