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Version 0.4.0 - 2022-06-29

This release includes the following updates

New Features

  • Add RewriteRollbackStrategy, SAPStrategy.
  • Redesign defense strategy API.
  • Add AdvTrainStrategy, SEMStrategy, SAPDStrategy

Version 0.3.1 - 2021-07-20

This release includes the following updates

New Features

  • Add dynamic_len seed option to ASRS, so the paraphrase can have different length.
  • Fix bug in asrs_utils_lm

Version 0.3.0 - 2021-06-05

This release includes the following updates

New Features

  • Rename BertSamplingStrategy model as ASRSStrategy.
  • Update ASRS to use Cross Encoder as default similarity metric.
  • Add timeout feature to TextAttackStrategy.
  • Update benchmark results.
  • Add paper reference.

Version 0.2.5 - 2021-03-22

This release is an emergency bug fix.

  • Fix the bug in DatasetForBert introduced by the previous update.

Version 0.2.4 - 2021-03-03

This release includes the following updates

New Features

  • Improve the doc string and documentation for adversarial training.
  • Add experimental code about non-autoregressive paraphrase strategy.

Version 0.2.3 - 2021-02-17

This release adds experimental code to adversarial training.

New Features

  • Add a default adversarial tuning strategy.
  • Add API in classifiers to support adversarial tuning.
  • Add args in benchmark for adversarial tuning.

Version 0.2.2 - 2021-02-03

This release fixes bugs and adds unit tests.

New Features

  • Add Sentence BERT metric and corresponding unit test.
  • Fix the bug of the colab demo.

Version 0.2.1 - 2021-01-20

This release improves documentation and unit tests.

New Features

  • Add integrity test for IdentityStrategy, TextAttackStrategy, and BertSamplingStrategy.
  • For IdentityStrategy and TextAttackStrategy, accuracy is verified.
  • Improve documentation, split data format from benchmark.

Version 0.2.0 - 2021-01-06

This release updates the structure of the project and improve documentation.

New Features

  • Metric module is redesigned to have a consistant API. (Issue #12)
  • More unit tests are added. Slow unit tests are skipped in CI. (Issue #11)
  • Benchmark table is updated. (Issue #10)
  • Better support to TextAttack. Users can choose any implemented attacking method in TextAttack using the ta_recipe arg. (Issue #9)

Version 0.1.3

This release includes the following updates:

  • Add a benchmark class. Users can integrate fibber benchmark to other projects. The class supports customized datasets, target classifier and attacking method.
  • Migrate from Travis CI to Github Action.
  • Move adversarial-attack-related aggragation functions from benchmark module to metric module.

Version 0.1.2

This minor release add pretrained classifiers and downloadable resources on a demo dataset, and a demo Colab.

Version 0.1.1

This minor release removes the dependency on textattack because it produces dependency conflicts. Users can install it manually to use attacking strategies in textattack.

version 0.1.0

This release is a major update to Fibber library. Advanced paraphrase algorithms are included.

  • Add two strategies: TextFoolerStrategy and BertSamplingStrategy.
  • Improve the benchmarking framework: add more metrics specifically designed for adversarial attack.
  • Datasets: add a variation of AG's news dataset, ag_no_title.
  • Bug fix and improvements.

version 0.0.1

This is the first release of Fibber library. This release contains:

  • Datasets: fibber contains 6 built-in datasets.
  • Metrics: fibber contains 6 metrics to evaluate the quality of paraphrased sentences. All metrics have a unified interface.
  • Benchmark framework: the benchmark framework and easily evaluate the phraphrase strategies on built-in datasets and metrics.
  • Strategies: this release contains 2 basic strategies, the identity strategy and random strategy.
  • A unified Fibber interface: users can easily use fibber by creating a Fibber object.