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Found 4 papers, 4 papers with code
RAFT: A Real-World Few-Shot Text Classification Benchmark
Will models soon solve classification tasks that have so far been reserved for human research assistants?
Ranked #2 on
Few-Shot Text Classification
on RAFT
Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples
We study the behavior of several black-box search algorithms used for generating adversarial examples for natural language processing (NLP) tasks.
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
TextAttack also includes data augmentation and adversarial training modules for using components of adversarial attacks to improve model accuracy and robustness.
Reevaluating Adversarial Examples in Natural Language
State-of-the-art attacks on NLP models lack a shared definition of a what constitutes a successful attack.
