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Found 21 papers, 8 papers with code
Personal Information Leakage Detection in Conversations
In this work, we propose to protect personal information by warning users of detected suspicious sentences generated by conversational assistants.
G3Detector: General GPT-Generated Text Detector
The burgeoning progress in the field of Large Language Models (LLMs) heralds significant benefits due to their unparalleled capacities.
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation
Modern NLP models are often trained over large untrusted datasets, raising the potential for a malicious adversary to compromise model behaviour.
Training-free Lexical Backdoor Attacks on Language Models
In this work, we propose Training-Free Lexical Backdoor Attack (TFLexAttack) as the first training-free backdoor attack on language models.
Rethinking Round-Trip Translation for Machine Translation Evaluation
Round-trip translation could be served as a clever and straightforward technique to alleviate the requirement of the parallel evaluation corpus.
Variational Autoencoder with Disentanglement Priors for Low-Resource Task-Specific Natural Language Generation
In this paper, we propose a variational autoencoder with disentanglement priors, VAE-DPRIOR, for task-specific natural language generation with none or a handful of task-specific labeled examples.
Protecting Intellectual Property of Language Generation APIs with Lexical Watermark
Nowadays, due to the breakthrough in natural language generation (NLG), including machine translation, document summarization, image captioning, etc NLG models have been encapsulated in cloud APIs to serve over half a billion people worldwide and process over one hundred billion word generations per day.
Humanly Certifying Superhuman Classifiers
In this paper, we first raise the challenge of evaluating the performance of both humans and models with respect to an oracle which is unobserved.
Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs
Machine-learning-as-a-service (MLaaS) has attracted millions of users to their splendid large-scale models.
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!
Finally, we investigate two defence strategies to protect the victim model and find that unless the performance of the victim model is sacrificed, both model ex-traction and adversarial transferability can effectively compromise the target models
Privacy-Aware Text Rewriting
Biased decisions made by automatic systems have led to growing concerns in research communities.
ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation
In this paper, we describe ALTER, an auxiliary text rewriting tool that facilitates the rewriting process for natural language generation tasks, such as paraphrasing, text simplification, fairness-aware text rewriting, and text style transfer.
D-PAGE: Diverse Paraphrase Generation
In this paper, we investigate the diversity aspect of paraphrase generation.
EPUTION at SemEval-2018 Task 2: Emoji Prediction with User Adaption
This paper describes our approach, called EPUTION, for the open trial of the SemEval- 2018 Task 2, Multilingual Emoji Prediction.
Demographic Inference on Twitter using Recursive Neural Networks
In social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one{'}s audience.
Collective Vertex Classification Using Recursive Neural Network
In this paper, we propose a graph-based recursive neural network framework for collective vertex classification.
Deep neural networks for learning graph representations
Different from other previous research efforts, we adopt a random surfing model to capture graph structural information directly, instead of using the sampling-based method for generating linear sequences proposed by Perozzi et al. (2014).
GraRep: Learning Graph Representations with Global Structural Information
In this paper, we present {GraRep}, a novel model for learning vertex representations of weighted graphs.
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