Search Results for author: Fanchao Qi

Found 36 papers, 32 papers with code

Going “Deeper”: Structured Sememe Prediction via Transformer with Tree Attention

1 code implementation Findings (ACL) 2022 Yining Ye, Fanchao Qi, Zhiyuan Liu, Maosong Sun

However, all existing sememe prediction studies ignore the hierarchical structures of sememes, which are important in the sememe-based semantic description system.

Pass off Fish Eyes for Pearls: Attacking Model Selection of Pre-trained Models

1 code implementation ACL 2022 Biru Zhu, Yujia Qin, Fanchao Qi, Yangdong Deng, Zhiyuan Liu, Maosong Sun, Ming Gu

To validate our viewpoints, we design two methods to evaluate the robustness of FMS: (1) model disguise attack, which post-trains an inferior PTM with a contrastive objective, and (2) evaluation data selection, which selects a subset of the data points for FMS evaluation based on K-means clustering.

Backdoor Attack Model Selection

Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

1 code implementation19 Oct 2022 Yangyi Chen, Hongcheng Gao, Ganqu Cui, Fanchao Qi, Longtao Huang, Zhiyuan Liu, Maosong Sun

We discuss the deficiencies in previous work and propose our suggestions that the research on the Security-oriented adversarial NLP (SoadNLP) should: (1) evaluate their methods on security tasks to demonstrate the real-world concerns; (2) consider real-world attackers' goals, instead of developing impractical methods.

Data Augmentation

QuoteR: A Benchmark of Quote Recommendation for Writing

1 code implementation ACL 2022 Fanchao Qi, Yanhui Yang, Jing Yi, Zhili Cheng, Zhiyuan Liu, Maosong Sun

To facilitate the research on this task, we build a large and fully open quote recommendation dataset called QuoteR, which comprises three parts including English, standard Chinese and classical Chinese.

Textual Backdoor Attacks Can Be More Harmful via Two Simple Tricks

1 code implementation15 Oct 2021 Yangyi Chen, Fanchao Qi, Hongcheng Gao, Zhiyuan Liu, Maosong Sun

In this paper, we find two simple tricks that can make existing textual backdoor attacks much more harmful.

Vocal Bursts Valence Prediction

Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer

1 code implementation EMNLP 2021 Fanchao Qi, Yangyi Chen, Xurui Zhang, Mukai Li, Zhiyuan Liu, Maosong Sun

In this paper, we make the first attempt to conduct adversarial and backdoor attacks based on text style transfer, which is aimed at altering the style of a sentence while preserving its meaning.

Backdoor Attack Style Transfer +1

CPM-2: Large-scale Cost-effective Pre-trained Language Models

2 code implementations20 Jun 2021 Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan YAO, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun

We present a suite of cost-effective techniques for the use of PLMs to deal with the efficiency issues of pre-training, fine-tuning, and inference.

Turn the Combination Lock: Learnable Textual Backdoor Attacks via Word Substitution

1 code implementation ACL 2021 Fanchao Qi, Yuan YAO, Sophia Xu, Zhiyuan Liu, Maosong Sun

Recent studies show that neural natural language processing (NLP) models are vulnerable to backdoor attacks.

CCPM: A Chinese Classical Poetry Matching Dataset

1 code implementation3 Jun 2021 Wenhao Li, Fanchao Qi, Maosong Sun, Xiaoyuan Yi, Jiarui Zhang

We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry.


Sub-Character Tokenization for Chinese Pretrained Language Models

2 code implementations1 Jun 2021 Chenglei Si, Zhengyan Zhang, Yingfa Chen, Fanchao Qi, Xiaozhi Wang, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun

2) Pronunciation-based SubChar tokenizers can encode Chinese homophones into the same transliteration sequences and produce the same tokenization output, hence being robust to homophone typos.

Chinese Word Segmentation Language Modelling +1

Automatic Construction of Sememe Knowledge Bases via Dictionaries

1 code implementation Findings (ACL) 2021 Fanchao Qi, Yangyi Chen, Fengyu Wang, Zhiyuan Liu, Xiao Chen, Maosong Sun

We use this method to build an English SKB and a French SKB, and conduct comprehensive evaluations from both intrinsic and extrinsic perspectives.

Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger

2 code implementations ACL 2021 Fanchao Qi, Mukai Li, Yangyi Chen, Zhengyan Zhang, Zhiyuan Liu, Yasheng Wang, Maosong Sun

As far as we know, almost all existing textual backdoor attack methods insert additional contents into normal samples as triggers, which causes the trigger-embedded samples to be detected and the backdoor attacks to be blocked without much effort.

Backdoor Attack

Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-Level Backdoor Attacks

1 code implementation ICML Workshop AML 2021 Zhengyan Zhang, Guangxuan Xiao, Yongwei Li, Tian Lv, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Xin Jiang, Maosong Sun

In this work, we demonstrate the universal vulnerability of PTMs, where fine-tuned PTMs can be easily controlled by backdoor attacks in arbitrary downstream tasks.

Backdoor Attack

Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning

1 code implementation31 Dec 2020 Chenglei Si, Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun

In this work, we propose a simple and effective method to cover a much larger proportion of the attack search space, called Adversarial and Mixup Data Augmentation (AMDA).

Adversarial Robustness Text Augmentation +2

Try to Substitute: An Unsupervised Chinese Word Sense Disambiguation Method Based on HowNet

1 code implementation COLING 2020 Bairu Hou, Fanchao Qi, Yuan Zang, Xurui Zhang, Zhiyuan Liu, Maosong Sun

In this paper, we propose a new unsupervised method for HowNet-based Chinese WSD, which exploits the masked language model task of pre-trained language models.

Language Modelling Word Sense Disambiguation

Know What You Don't Need: Single-Shot Meta-Pruning for Attention Heads

no code implementations7 Nov 2020 Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Qun Liu, Maosong Sun

To measure the informativeness of attention heads, we train our Single-Shot Meta-Pruner (SMP) with a meta-learning paradigm aiming to maintain the distribution of text representations after pruning.

Informativeness Meta-Learning +1

WantWords: An Open-source Online Reverse Dictionary System

1 code implementation EMNLP 2020 Fanchao Qi, Lei Zhang, Yanhui Yang, Zhiyuan Liu, Maosong Sun

A reverse dictionary takes descriptions of words as input and outputs words semantically matching the input descriptions.

Reverse Dictionary

Country Image in COVID-19 Pandemic: A Case Study of China

1 code implementation12 Sep 2020 Huimin Chen, Zeyu Zhu, Fanchao Qi, Yining Ye, Zhiyuan Liu, Maosong Sun, Jianbin Jin

Therefore, in this study, we take China as a specific and typical case and investigate its image with aspect-based sentiment analysis on a large-scale Twitter dataset.

Aspect-Based Sentiment Analysis (ABSA)

Lexical Sememe Prediction using Dictionary Definitions by Capturing Local Semantic Correspondence

1 code implementation16 Jan 2020 Jiaju Du, Fanchao Qi, Maosong Sun, Zhiyuan Liu

We find that sememes of each word are usually semantically matched to different words in its dictionary definition, and we name this matching relationship local semantic correspondence.

Semantic correspondence

Multi-channel Reverse Dictionary Model

1 code implementation18 Dec 2019 Lei Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun

A reverse dictionary takes the description of a target word as input and outputs the target word together with other words that match the description.

Reverse Dictionary

Word-level Textual Adversarial Attacking as Combinatorial Optimization

1 code implementation ACL 2020 Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, Maosong Sun

Also, further experiments show our model has higher transferability and can bring more robustness enhancement to victim models by adversarial training.

Adversarial Attack Combinatorial Optimization +3

Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes

1 code implementation20 Oct 2019 Yujia Qin, Fanchao Qi, Sicong Ouyang, Zhiyuan Liu, Cheng Yang, Yasheng Wang, Qun Liu, Maosong Sun

Sememes, the minimum semantic units of human languages, have been successfully utilized in various natural language processing applications.

Adversarial Attack Language Modelling +2

Using BERT for Word Sense Disambiguation

no code implementations18 Sep 2019 Jiaju Du, Fanchao Qi, Maosong Sun

Word Sense Disambiguation (WSD), which aims to identify the correct sense of a given polyseme, is a long-standing problem in NLP.

Word Sense Disambiguation

Modeling Semantic Compositionality with Sememe Knowledge

1 code implementation ACL 2019 Fanchao Qi, Jun-Jie Huang, Chenghao Yang, Zhiyuan Liu, Xiao Chen, Qun Liu, Maosong Sun

In this paper, we verify the effectiveness of sememes, the minimum semantic units of human languages, in modeling SC by a confirmatory experiment.

multi-word expression embedding multi-word expression sememe prediction

COS960: A Chinese Word Similarity Dataset of 960 Word Pairs

1 code implementation1 Jun 2019 Junjie Huang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Maosong Sun

Word similarity computation is a widely recognized task in the field of lexical semantics.

POS Word Similarity

OpenHowNet: An Open Sememe-based Lexical Knowledge Base

1 code implementation28 Jan 2019 Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Qiang Dong, Maosong Sun, Zhendong Dong

In this paper, we present an open sememe-based lexical knowledge base OpenHowNet.

Cross-lingual Lexical Sememe Prediction

1 code implementation EMNLP 2018 Fanchao Qi, Yankai Lin, Maosong Sun, Hao Zhu, Ruobing Xie, Zhiyuan Liu

We propose a novel framework to model correlations between sememes and multi-lingual words in low-dimensional semantic space for sememe prediction.

Learning Word Embeddings Multilingual Word Embeddings

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