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Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
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Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ...
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STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.251/ Abstract: Recent studies have shown that deep neural network-based models are vulnerable to intentionally crafted adversarial examples, and various methods have been proposed to defend against adversarial word-substitution attacks for neural NLP models. However, there is a lack of systematic study on comparing different defense approaches under the same attacking setting. In this paper, we seek to fill the gap through comprehensive studies on the behavior of neural text classifiers trained with various defense methods against representative adversarial attacks. In addition, we propose an effective method to further improve the robustness of neural text classifiers against such attacks, and achieved the highest accuracy on both clean and adversarial examples on AGNEWS and IMDB datasets, outperforming existing methods by a significant margin. We hope this study could provide useful clues for future research on text adversarial defense. Codes ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Neural Network
URL: https://dx.doi.org/10.48448/tmch-e809
https://underline.io/lecture/38025-searching-for-an-effective-defender-benchmarking-defense-against-adversarial-word-substitution
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Graphine: A Dataset for Graph-aware Terminology Definition Generation ...
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6
End-to-end style-conditioned poetry generation: What does it take to learn from examples alone? ...
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7
To what extent do human explanations of model behavior align with actual model behavior? ...
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8
Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs ...
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9
What’s Hidden in a One-layer Randomly Weighted Transformer? ...
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10
Finetuning Pretrained Transformers into RNNs ...
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11
Sometimes We Want Ungrammatical Translations ...
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12
Pruning Neural Machine Translation for Speed Using Group Lasso ...
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13
Elementary-Level Math Word Problem Generation using Pre-Trained Transformers ...
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14
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings ...
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15
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation ...
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16
Knowledge Graph Representation Learning using Ordinary Differential Equations ...
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17
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations ...
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18
Mind the Context: The Impact of Contextualization in Neural Module Networks for Grounding Visual Referring Expressions ...
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19
EM ALBERT: a step towards equipping Manipuri for NLP ...
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20
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection ...
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