State-of-the-art machine learning models are prone to adversarial attacks: Maliciously crafted inputs to fool the model into making a wrong prediction, often with high confidence. While defense strategies have been extensively explored in the computer vision domain, re- search in natural language processing still lacks techniques to make models resilient to adver- sarial text inputs. We adapt a technique from computer vision to detect word-level attacks targeting text classifiers. This method relies on training an adversarial detector leveraging Shapley additive explanations and outperforms the current state-of-the-art on two benchmarks. Furthermore, we prove the detector requires only a low amount of training samples and, in some cases, generalizes to different datasets without needing to retrain.

Detecting Word-Level Adversarial Text Attacks via SHapley Additive exPlanations

**Organizers:** Spandana Gella, He He, Burcu Can, Maximilian Mozes, Eleonora Giunchiglia, Sewon Min,
Samuel Cahyawijaya, Xiang Lorraine Li and Bodhisattwa Prasad Majumder **Description:** The 7th Workshop on Representation Learning for NLP (RepL4NLP 2022) will be hosted by ACL 2022 and held on
26 May 2022. The workshop is being organised by Spandana Gella, He He, Burcu Can, Maximilian Mozes, Eleonora
Giunchiglia, Sewon Min, Samuel Cahyawijaya, Xiang Lorraine Li and Bodhisattwa Prasad Majumder; and advised by
Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Chris Dyer and Laura Rimell. The workshop
is organised by the ACL Special Interest Group on Representation Learning (SIGREP). The 7th Workshop on Representation Learning for NLP aims to continue the success of the Repl4NLP workshop series, with the 1st Workshop
on Representation Learning for NLP having received about 50 submissions and over 250 attendees – the second most
attended collocated event at ACL’16 after WMT). The workshop was introduced as a synthesis of several years of independent ACL workshops focusing on vector space models of meaning, compositionality, and the application of deep
neural networks and spectral methods to NLP. It provides a forum for discussing recent advances on these topics, as well
as future research directions in linguistically motivated vector-based models in NLP. The workshop will take place in a
hybrid setting, and, as in previous years, feature interdisciplinary keynotes, paper presentations, posters, as well as a panel
discussion. 
**Please visit our [website](https://sites.google.com/view/repl4nlp2022/)**

(RepL4NLP)        7th Workshop on Representation Learning for NLP

workshop paper

# Welcome everyone to ACL 2022!

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ACL 2022

The Association for Computational Linguistics (ACL) is the premier international scientific and professional society for people working on computational problems involving human language, a field often referred to as either computational linguistics or natural language processing (NLP). 

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Detecting Word-Level Adversarial Text Attacks via SHapley Additive exPlanations

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