SPARTA

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[EACL 2026] SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space

SPARTA 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# SPARTA

**Official Implementation of "SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space"**

[![arXiv](https://img.shields.io/badge/arXiv-2510.24446-b31b1b.svg)](https://arxiv.org/abs/2510.24446)
[![Python 3.10](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/release/python-31016/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

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---

## 📢 News

> 🚧 **More updates coming soon!** Stay tuned for additional features, documentation, and improvements.

---

## 📋 Overview

This repository contains the official implementation of the paper **SPARTA** (arXiv:2510.24446).

## 🚀 Getting Started

### Installation

```cmd
# create conda env
conda create -n rtext python==3.10.16
conda activate rtext
#  install python packages
pip install -r requirements-attack.txt
pip install -e fairseq2
pip install -e SONAR
pip install -e LISA
pip install -e LISA_v0
pip install -e GSVA
pip install -e rtext
```

SPARTA

SPARTA 최신버젼 다운로드

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SPARTA

SPARTA 최신버젼 다운로드

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