OpenAttack VS KitanaQA

Compare OpenAttack vs KitanaQA and see what are their differences.

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OpenAttack KitanaQA
1 1
652 57
1.5% -
0.0 0.0
10 months ago 10 months ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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OpenAttack

Posts with mentions or reviews of OpenAttack. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-07-06.
  • TextAttack VS OpenAttack - a user suggested alternative
    2 projects | 6 Jul 2022
    Similar to TextAttack, OpenAttack adopts modular design to assemble various attack models, in order to enable quick implementation of existing or new attack models. But OpenAttack is different from and complementary to TextAttack mainly in the following three aspects: 1) Support for all attacks. TextAttack utilizes a relatively rigorous framework to unify different attack models. However, this framework is naturally not suitable for sentence-level adversarial attacks, an important and typical kind of textual adversarial attacks. Thus, no sentence-level attack models are included in TextAttack. In contrast, OpenAttack adopts a more flexible framework that supports all types of attacks including sentence-level attacks. 2) Multilinguality. TextAttack only covers English textual attacks while OpenAttack supports English and Chinese now. And its extensible design enables quick support for more languages. 3) Parallel processing. Running some attack models maybe very time-consuming, e.g., it takes over 100 seconds to attack an instance with the SememePSO attack model (Zang et al., 2020). To address this issue, OpenAttack additionally provides support for multi-process running of attack models to improve attack efficiency.

KitanaQA

Posts with mentions or reviews of KitanaQA. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-01.
  • Ask HN: Who is hiring? (February 2021)
    16 projects | news.ycombinator.com | 1 Feb 2021
    Searchable.ai | Full Stack Engineer | Full Time | Remote U.S.

    We help our users find their stuff wherever it's stored as we build the future of enterprise search.

    We are hiring a full-stack engineer with Rails experience to join our growing engineering team. Our stack includes: Rails, Electron, Webpack, PostgreSQL, Elasticsearch & Kubernetes.

    This position will also have the opportunity to help integrate our research teams' SOTA work into our product to help users ask questions across their files (see: https://github.com/searchableai/kitanaqa).

    Full description here: https://www.searchable.ai/full-stack-engineer/ and drop us a line at careers at searchable dot ai if you're interested!

What are some alternatives?

When comparing OpenAttack and KitanaQA you can also consider the following projects:

TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

allennlp - An open-source NLP research library, built on PyTorch.

FinBERT-QA - Financial Domain Question Answering with pre-trained BERT Language Model

flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)

akvo-flow - A data collection and monitoring tool that works anywhere.

ozone - Scalable, redundant, and distributed object store for Apache Hadoop

auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

eClaire - Trello card printer

inltk - Natural Language Toolkit for Indic Languages aims to provide out of the box support for various NLP tasks that an application developer might need

bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

jina - ☁️ Build multimodal AI applications with cloud-native stack