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NLP2CT / DetectRL
Forked from junchaoIU/DetectRL[NeurIPS 2024 D&B] DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios
This repo is a collection of AWESOME things about fake news detection, including papers, code, etc.
[ICML 2024] COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability
Collection of extracted System Prompts from popular chatbots like ChatGPT, Claude & Gemini
Tools for merging pretrained large language models.
Resource library for getting started with deep learning work using electrocardiograms
③[ICML2024] [IQA, IAA, VQA] All-in-one Foundation Model for visual scoring. Can efficiently fine-tune to downstream datasets.
💻 A curated list of papers and resources for multi-modal Graphical User Interface (GUI) agents.
A curated list of of awesome UI agents resources, encompassing Web, App, OS, and beyond (continually updated)
Fully open reproduction of DeepSeek-R1
Training-free LLM-generated Text Detection by Mining Token Probability Sequences (ICLR 2025)
This repository contains a collection of resources and papers on Detecting Multimedia Generated by Large AI Models
A modular graph-based Retrieval-Augmented Generation (RAG) system
✨✨Latest Advances on Multimodal Large Language Models
A collection of benchmarks and datasets for evaluating LLM.
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
[TMLR] A curated list of language modeling researches for code (and other software engineering activities), plus related datasets.
Interpretability and explainability of data and machine learning models
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Official repository for our NeurIPS 2023 paper "Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense" (https://arxiv.org/abs/2303.13408).
本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）