Search Results for author: Hai-Tao Zheng

Found 75 papers, 35 papers with code

Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark

1 code implementation29 Feb 2024 Zhikun Xu, Yinghui Li, Ruixue Ding, Xinyu Wang, Boli Chen, Yong Jiang, Xiaodong Deng, Jianxin Ma, Hai-Tao Zheng, Wenlian Lu, Pengjun Xie, Chang Zhou, Fei Huang

To promote the improvement of Chinese LLMs' ability to answer dynamic questions, in this paper, we introduce CDQA, a Chinese Dynamic QA benchmark containing question-answer pairs related to the latest news on the Chinese Internet.

Question Answering

Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction

no code implementations18 Feb 2024 Yinghui Li, Shang Qin, Jingheng Ye, Shirong Ma, Yangning Li, Libo Qin, Xuming Hu, Wenhao Jiang, Hai-Tao Zheng, Philip S. Yu

To promote the CGEC field to better adapt to the era of LLMs, we rethink the roles of LLMs in the CGEC task so that they can be better utilized and explored in CGEC.

Grammatical Error Correction

When LLMs Meet Cunning Questions: A Fallacy Understanding Benchmark for Large Language Models

no code implementations16 Feb 2024 Yinghui Li, Qingyu Zhou, Yuanzhen Luo, Shirong Ma, Yangning Li, Hai-Tao Zheng, Xuming Hu, Philip S. Yu

In this paper, we challenge the reasoning and understanding abilities of LLMs by proposing a FaLlacy Understanding Benchmark (FLUB) containing cunning questions that are easy for humans to understand but difficult for models to grasp.

EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data

no code implementations25 Dec 2023 Shirong Ma, Shen Huang, Shulin Huang, Xiaobin Wang, Yangning Li, Hai-Tao Zheng, Pengjun Xie, Fei Huang, Yong Jiang

Experimental results demonstrate the effectiveness of continual pre-training of E-commerce LLMs and the efficacy of our devised data mixing strategy.

In-Context Learning

RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

1 code implementation1 Dec 2023 Tianyu Yu, Yuan YAO, Haoye Zhang, Taiwen He, Yifeng Han, Ganqu Cui, Jinyi Hu, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun, Tat-Seng Chua

Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction.

Hallucination

Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters

no code implementations19 Nov 2023 Yinghui Li, Zishan Xu, Shaoshen Chen, Haojing Huang, Yangning Li, Yong Jiang, Zhongli Li, Qingyu Zhou, Hai-Tao Zheng, Ying Shen

To the best of our knowledge, Visual-C$^3$ is the first real-world visual and the largest human-crafted dataset for the Chinese character checking scenario.

A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check

1 code implementation13 Oct 2023 Haojing Huang, Jingheng Ye, Qingyu Zhou, Yinghui Li, Yangning Li, Feng Zhou, Hai-Tao Zheng

In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task in an end-to-end fashion.

Reformulating Vision-Language Foundation Models and Datasets Towards Universal Multimodal Assistants

2 code implementations1 Oct 2023 Tianyu Yu, Jinyi Hu, Yuan YAO, Haoye Zhang, Yue Zhao, Chongyi Wang, Shan Wang, Yinxv Pan, Jiao Xue, Dahai Li, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun

The capabilities of MLLMs depend on two crucial factors: the model architecture to facilitate the feature alignment of visual modules and large language models; the multimodal instruction tuning datasets for human instruction following.

Instruction Following

Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection

no code implementations10 Sep 2023 Chaiyut Luoyiching, Yangning Li, Yinghui Li, Rongsheng Li, Hai-Tao Zheng, Nannan Zhou, Hanjing Su

Previous GFSID methods rely on the episodic learning paradigm, which makes it hard to extend to a generalized setup as they do not explicitly learn the classification of seen categories and the knowledge of seen intents.

Class Incremental Learning Incremental Learning +1

Retrieval-Augmented Meta Learning for Low-Resource Text Classification

no code implementations10 Sep 2023 Rongsheng Li, Yangning Li, Yinghui Li, Chaiyut Luoyiching, Hai-Tao Zheng, Nannan Zhou, Hanjing Su

However, due to the limited training data in the meta-learning scenario and the inherent properties of parameterized neural networks, poor generalization performance has become a pressing problem that needs to be addressed.

Meta-Learning Retrieval +2

An Anchor Learning Approach for Citation Field Learning

no code implementations7 Sep 2023 Zilin Yuan, Borun Chen, Yimeng Dai, Yinghui Li, Hai-Tao Zheng, Rui Zhang

CIFAL leverages the anchor learning, which is model-agnostic for any Pre-trained Language Model, to help capture citation patterns from the data of different citation styles.

Language Modelling Sentence

MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

1 code implementation22 Aug 2023 Jinpeng Wang, Ziyun Zeng, Yunxiao Wang, Yuting Wang, Xingyu Lu, Tianxiang Li, Jun Yuan, Rui Zhang, Hai-Tao Zheng, Shu-Tao Xia

We propose MISSRec, a multi-modal pre-training and transfer learning framework for SR. On the user side, we design a Transformer-based encoder-decoder model, where the contextual encoder learns to capture the sequence-level multi-modal user interests while a novel interest-aware decoder is developed to grasp item-modality-interest relations for better sequence representation.

Contrastive Learning Sequential Recommendation +1

LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles

1 code implementation21 Aug 2023 Shulin Huang, Shirong Ma, Yinghui Li, Mengzuo Huang, Wuhe Zou, Weidong Zhang, Hai-Tao Zheng

With the continuous evolution and refinement of LLMs, they are endowed with impressive logical reasoning or vertical thinking capabilities.

Logical Reasoning

EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce

1 code implementation14 Aug 2023 Yangning Li, Shirong Ma, Xiaobin Wang, Shen Huang, Chengyue Jiang, Hai-Tao Zheng, Pengjun Xie, Fei Huang, Yong Jiang

EcomInstruct scales up the data size and task diversity by constructing atomic tasks with E-commerce basic data types, such as product information, user reviews.

Instruction Following Language Modelling +2

MESED: A Multi-modal Entity Set Expansion Dataset with Fine-grained Semantic Classes and Hard Negative Entities

1 code implementation27 Jul 2023 Yangning Li, Tingwei Lu, Yinghui Li, Tianyu Yu, Shulin Huang, Hai-Tao Zheng, Rui Zhang, Jun Yuan

The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new entities belonging to the same semantic class.

On the (In)Effectiveness of Large Language Models for Chinese Text Correction

no code implementations18 Jul 2023 Yinghui Li, Haojing Huang, Shirong Ma, Yong Jiang, Yangning Li, Feng Zhou, Hai-Tao Zheng, Qingyu Zhou

Recently, the development and progress of Large Language Models (LLMs) have amazed the entire Artificial Intelligence community.

Grammatical Error Correction

Progressive Multi-task Learning Framework for Chinese Text Error Correction

no code implementations30 Jun 2023 Shirong Ma, Yinghui Li, Haojing Huang, Shulin Huang, Yangning Li, Hai-Tao Zheng, Ying Shen

To mitigate the issue of overcorrection, we propose a novel model-agnostic progressive multitask learning framework for CTEC, named ProTEC, which guides a CTEC model to learn the task from easy to difficult.

Multi-Task Learning

AOG-LSTM: An adaptive attention neural network for visual storytelling

no code implementations Neurocomputing 2023 Hanqing Liu, Jiacheng Yang, Chia-Hao Chang, Wei Wang, Hai-Tao Zheng, Yong Jiang, Hui Wang, Rui Xie, and Wei Wu

Moreover, the existing method of alleviating error accumulation based on replacing reference words does not take into account the different effects of each word.

Visual Storytelling

Mining Interest Trends and Adaptively Assigning SampleWeight for Session-based Recommendation

no code implementations20 Jun 2023 Kai Ouyang, Xianghong Xu, Miaoxin Chen, Zuotong Xie, Hai-Tao Zheng, Shuangyong Song, Yu Zhao

Session-based Recommendation (SR) aims to predict users' next click based on their behavior within a short period, which is crucial for online platforms.

Session-Based Recommendations

Exploring Lottery Prompts for Pre-trained Language Models

no code implementations31 May 2023 Yulin Chen, Ning Ding, Xiaobin Wang, Shengding Hu, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie

Consistently scaling pre-trained language models (PLMs) imposes substantial burdens on model adaptation, necessitating more efficient alternatives to conventional fine-tuning.

CLEME: Debiasing Multi-reference Evaluation for Grammatical Error Correction

2 code implementations18 May 2023 Jingheng Ye, Yinghui Li, Qingyu Zhou, Yangning Li, Shirong Ma, Hai-Tao Zheng, Ying Shen

Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging task due to its subjectivity.

Grammatical Error Correction

Knowledge Soft Integration for Multimodal Recommendation

no code implementations12 May 2023 Kai Ouyang, Chen Tang, Wenhao Zheng, Xiangjin Xie, Xuanji Xiao, Jian Dong, Hai-Tao Zheng, Zhi Wang

To address this issue, we propose using knowledge soft integration to balance the utilization of multimodal features and the curse of knowledge problem it brings about.

Multimodal Recommendation Retrieval

From Retrieval to Generation: Efficient and Effective Entity Set Expansion

no code implementations7 Apr 2023 Shulin Huang, Shirong Ma, Yangning Li, Yinghui Li, Yong Jiang, Hai-Tao Zheng, Ying Shen

For efficiency, expansion time consumed by GenExpan is independent of entity vocabulary and corpus size, and GenExpan achieves an average 600% speedup compared to strong baselines.

Language Modelling Retrieval

MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs

1 code implementation5 Apr 2023 Jifan Yu, Mengying Lu, Qingyang Zhong, Zijun Yao, Shangqing Tu, Zhengshan Liao, Xiaoya Li, Manli Li, Lei Hou, Hai-Tao Zheng, Juanzi Li, Jie Tang

Student modeling, the task of inferring a student's learning characteristics through their interactions with coursework, is a fundamental issue in intelligent education.

cognitive diagnosis Knowledge Tracing

Click-aware Structure Transfer with Sample Weight Assignment for Post-Click Conversion Rate Estimation

no code implementations3 Apr 2023 Kai Ouyang, Wenhao Zheng, Chen Tang, Xuanji Xiao, Hai-Tao Zheng

To tackle this issue, we argue that a trade-off should be achieved between the introduction of large amounts of auxiliary information and the protection of valuable information related to CVR.

Multi-Task Learning

Enhancing Text Generation with Cooperative Training

1 code implementation16 Mar 2023 Tong Wu, Hao Wang, Zhongshen Zeng, Wei Wang, Hai-Tao Zheng, Jiaxing Zhang

Recently, there has been a surge in the use of generated data to enhance the performance of downstream models, largely due to the advancements in pre-trained language models.

MRPC QQP +2

Knowledge-augmented Few-shot Visual Relation Detection

no code implementations9 Mar 2023 Tianyu Yu, Yangning Li, Jiaoyan Chen, Yinghui Li, Hai-Tao Zheng, Xi Chen, Qingbin Liu, Wenqiang Liu, Dongxiao Huang, Bei Wu, Yexin Wang

Inspired by this, we devise a knowledge-augmented, few-shot VRD framework leveraging both textual knowledge and visual relation knowledge to improve the generalization ability of few-shot VRD.

Few-Shot Learning Language Modelling +1

Establishing a stronger baseline for lightweight contrastive models

1 code implementation14 Dec 2022 Wenye Lin, Yifeng Ding, Zhixiong Cao, Hai-Tao Zheng

A common practice to address this problem is to introduce a pretrained contrastive teacher model and train the lightweight networks with distillation signals generated by the teacher.

Contrastive Learning

Visually Grounded Commonsense Knowledge Acquisition

1 code implementation22 Nov 2022 Yuan YAO, Tianyu Yu, Ao Zhang, Mengdi Li, Ruobing Xie, Cornelius Weber, Zhiyuan Liu, Hai-Tao Zheng, Stefan Wermter, Tat-Seng Chua, Maosong Sun

In this work, we present CLEVER, which formulates CKE as a distantly supervised multi-instance learning problem, where models learn to summarize commonsense relations from a bag of images about an entity pair without any human annotation on image instances.

Language Modelling

Embracing Ambiguity: Improving Similarity-oriented Tasks with Contextual Synonym Knowledge

no code implementations20 Nov 2022 Yangning Li, Jiaoyan Chen, Yinghui Li, Tianyu Yu, Xi Chen, Hai-Tao Zheng

Extensive experiments demonstrate that PICSO can dramatically outperform the original PLMs and the other knowledge and synonym injection models on four different similarity-oriented tasks.

Entity Linking Language Modelling +4

Few-shot Classification with Hypersphere Modeling of Prototypes

no code implementations10 Nov 2022 Ning Ding, Yulin Chen, Ganqu Cui, Xiaobin Wang, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie

Moreover, it is more convenient to perform metric-based classification with hypersphere prototypes than statistical modeling, as we only need to calculate the distance from a data point to the surface of the hypersphere.

Classification Few-Shot Learning +1

Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation

1 code implementation29 Oct 2022 Shulin Huang, Shirong Ma, Yinghui Li, Yangning Li, Shiyang Lin, Hai-Tao Zheng, Ying Shen

Facing this dilemma, we focus on a novel CTG scenario, i. e., blessing generation which is challenging because high-quality blessing texts require CTG models to comprehensively consider the entanglement between multiple attributes (e. g., objects and occasions).

Attribute Text Generation

A Curriculum Learning Approach for Multi-domain Text Classification Using Keyword weight Ranking

no code implementations27 Oct 2022 Zilin Yuan, Yinghui Li, Yangning Li, Rui Xie, Wei Wu, Hai-Tao Zheng

We noted that the distinctness of the domain-specific features is different, so in this paper, we propose to use a curriculum learning strategy based on keyword weight ranking to improve the performance of multi-domain text classification models.

text-classification Text Classification

Focus Is What You Need For Chinese Grammatical Error Correction

no code implementations23 Oct 2022 Jingheng Ye, Yinghui Li, Shirong Ma, Rui Xie, Wei Wu, Hai-Tao Zheng

Chinese Grammatical Error Correction (CGEC) aims to automatically detect and correct grammatical errors contained in Chinese text.

Grammatical Error Correction Sentence

Automatic Context Pattern Generation for Entity Set Expansion

1 code implementation17 Jul 2022 Yinghui Li, Shulin Huang, Xinwei Zhang, Qingyu Zhou, Yangning Li, Ruiyang Liu, Yunbo Cao, Hai-Tao Zheng, Ying Shen

In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities.

Information Retrieval Retrieval +1

Contrastive Learning with Hard Negative Entities for Entity Set Expansion

1 code implementation16 Apr 2022 Yinghui Li, Yangning Li, Yuxin He, Tianyu Yu, Ying Shen, Hai-Tao Zheng

In addition, we propose the ProbExpan, a novel probabilistic ESE framework utilizing the entity representation obtained by the aforementioned language model to expand entities.

Contrastive Learning Language Modelling

Efficient Sub-structured Knowledge Distillation

1 code implementation9 Mar 2022 Wenye Lin, Yangming Li, Lemao Liu, Shuming Shi, Hai-Tao Zheng

Specifically, we transfer the knowledge from a teacher model to its student model by locally matching their predictions on all sub-structures, instead of the whole output space.

Knowledge Distillation Structured Prediction

Are we ready for a new paradigm shift? A Survey on Visual Deep MLP

1 code implementation7 Nov 2021 Ruiyang Liu, Yinghui Li, Linmi Tao, Dun Liang, Hai-Tao Zheng

In the GPU era, the locally and globally weighted summations are the current mainstreams, represented by the convolution and self-attention mechanism, as well as MLP.

OpenPrompt: An Open-source Framework for Prompt-learning

2 code implementations ACL 2022 Ning Ding, Shengding Hu, Weilin Zhao, Yulin Chen, Zhiyuan Liu, Hai-Tao Zheng, Maosong Sun

Prompt-learning has become a new paradigm in modern natural language processing, which directly adapts pre-trained language models (PLMs) to $cloze$-style prediction, autoregressive modeling, or sequence to sequence generation, resulting in promising performances on various tasks.

A non-hierarchical attention network with modality dropout for textual response generation in multimodal dialogue systems

no code implementations19 Oct 2021 Rongyi Sun, Borun Chen, Qingyu Zhou, Yinghui Li, Yunbo Cao, Hai-Tao Zheng

Existing text- and image-based multimodal dialogue systems use the traditional Hierarchical Recurrent Encoder-Decoder (HRED) framework, which has an utterance-level encoder to model utterance representation and a context-level encoder to model context representation.

Response Generation

Few-shot Learning with Big Prototypes

no code implementations29 Sep 2021 Ning Ding, Yulin Chen, Xiaobin Wang, Hai-Tao Zheng, Zhiyuan Liu, Pengjun Xie

A big prototype could be effectively modeled by two sets of learnable parameters, one is the center of the hypersphere, which is an embedding with the same dimension of training examples.

Few-Shot Learning

Prompt-Learning for Fine-Grained Entity Typing

no code implementations24 Aug 2021 Ning Ding, Yulin Chen, Xu Han, Guangwei Xu, Pengjun Xie, Hai-Tao Zheng, Zhiyuan Liu, Juanzi Li, Hong-Gee Kim

In this work, we investigate the application of prompt-learning on fine-grained entity typing in fully supervised, few-shot and zero-shot scenarios.

Entity Typing Knowledge Probing +5

Sentence Semantic Regression for Text Generation

no code implementations6 Aug 2021 Wei Wang, Piji Li, Hai-Tao Zheng

In the phase of surface realization, a mixed-granularity sentence decoder is designed to generate text with better consistency by jointly incorporating the predicted sentence-level main idea as well as the preceding contextual token-level information.

Dialogue Generation Language Modelling +2

CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding

1 code implementation ACL 2021 Dong Wang, Ning Ding, Piji Li, Hai-Tao Zheng

Recent works aimed to improve the robustness of pre-trained models mainly focus on adversarial training from perturbed examples with similar semantics, neglecting the utilization of different or even opposite semantics.

Contrastive Learning Natural Language Understanding +3

Few-NERD: A Few-Shot Named Entity Recognition Dataset

7 code implementations ACL 2021 Ning Ding, Guangwei Xu, Yulin Chen, Xiaobin Wang, Xu Han, Pengjun Xie, Hai-Tao Zheng, Zhiyuan Liu

In this paper, we present Few-NERD, a large-scale human-annotated few-shot NER dataset with a hierarchy of 8 coarse-grained and 66 fine-grained entity types.

Few-shot NER Named Entity Recognition

Learning Purified Feature Representations from Task-irrelevant Labels

no code implementations22 Feb 2021 Yinghui Li, Chen Wang, Yangning Li, Hai-Tao Zheng, Ying Shen

Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks.

Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection

no code implementations13 Feb 2021 Wei Wang, Piji Li, Hai-Tao Zheng

Automatic comment generation is a special and challenging task to verify the model ability on news content comprehension and language generation.

Clustering Comment Generation +2

Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation

no code implementations20 Jan 2021 Lingyun Feng, Minghui Qiu, Yaliang Li, Hai-Tao Zheng, Ying Shen

Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications.

Knowledge Distillation

Consistency and Coherency Enhanced Story Generation

no code implementations17 Oct 2020 Wei Wang, Piji Li, Hai-Tao Zheng

In terms of consistency, on one hand, GPT2 cannot guarantee the consistency of the plots explicitly.

Language Modelling Story Generation

Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation

1 code implementation ACL 2020 Ning Ding, Dingkun Long, Guangwei Xu, Muhua Zhu, Pengjun Xie, Xiaobin Wang, Hai-Tao Zheng

In order to simultaneously alleviate these two issues, this paper proposes to couple distant annotation and adversarial training for cross-domain CWS.

Chinese Word Segmentation Sentence

Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box Attacks

1 code implementation24 Jun 2020 Huiying Li, Shawn Shan, Emily Wenger, Jiayun Zhang, Hai-Tao Zheng, Ben Y. Zhao

In particular, query-based black-box attacks do not require knowledge of the deep learning model, but can compute adversarial examples over the network by submitting queries and inspecting returns.

Image Classification text-classification +1

The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection

no code implementations EMNLP 2020 Zibo Lin, Deng Cai, Yan Wang, Xiaojiang Liu, Hai-Tao Zheng, Shuming Shi

Despite that response selection is naturally a learning-to-rank problem, most prior works take a point-wise view and train binary classifiers for this task: each response candidate is labeled either relevant (one) or irrelevant (zero).

Conversational Response Selection Learning-To-Rank +2

Fawkes: Protecting Privacy against Unauthorized Deep Learning Models

1 code implementation19 Feb 2020 Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Hai-Tao Zheng, Ben Y. Zhao

In this paper, we propose Fawkes, a system that helps individuals inoculate their images against unauthorized facial recognition models.

Face Recognition Privacy Preserving Deep Learning

Event Detection with Trigger-Aware Lattice Neural Network

1 code implementation IJCNLP 2019 Ning Ding, Ziran Li, Zhiyuan Liu, Hai-Tao Zheng, Zibo Lin

To ad- dress the two issues simultaneously, we pro- pose the Trigger-aware Lattice Neural Net- work (TLNN).

Event Detection

CARL: Aggregated Search with Context-Aware Module Embedding Learning

no code implementations3 Aug 2019 Xinting Huang, Jianzhong Qi, Yu Sun, Rui Zhang, Hai-Tao Zheng

To model and utilize the context information for aggregated search, we propose a model with context attention and representation learning (CARL).

Representation Learning

Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge

1 code implementation ACL 2019 Ziran Li, Ning Ding, Zhiyuan Liu, Hai-Tao Zheng, Ying Shen

Chinese relation extraction is conducted using neural networks with either character-based or word-based inputs, and most existing methods typically suffer from segmentation errors and ambiguity of polysemy.

Relation Relation Extraction +1

Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks

no code implementations24 May 2019 Yuanshun Yao, Huiying Li, Hai-Tao Zheng, Ben Y. Zhao

Recent work has proposed the concept of backdoor attacks on deep neural networks (DNNs), where misbehaviors are hidden inside "normal" models, only to be triggered by very specific inputs.

Backdoor Attack Traffic Sign Recognition +1

Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks

1 code implementation18 Apr 2019 Shawn Shan, Emily Wenger, Bolun Wang, Bo Li, Hai-Tao Zheng, Ben Y. Zhao

Attackers' optimization algorithms gravitate towards trapdoors, leading them to produce attacks similar to trapdoors in the feature space.

Adversarial Attack Detection Adversarial Defense +3

Addressing Training Bias via Automated Image Annotation

no code implementations22 Sep 2018 Zhujun Xiao, Yanzi Zhu, Yuxin Chen, Ben Y. Zhao, Junchen Jiang, Hai-Tao Zheng

Build accurate DNN models requires training on large labeled, context specific datasets, especially those matching the target scenario.

Automated Crowdturfing Attacks and Defenses in Online Review Systems

no code implementations27 Aug 2017 Yuanshun Yao, Bimal Viswanath, Jenna Cryan, Hai-Tao Zheng, Ben Y. Zhao

Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers.

Cryptography and Security Social and Information Networks

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