Search Results for author: Hai-Tao Zheng

Found 33 papers, 15 papers with code

Automatic Context Pattern Generation for Entity Set Expansion

no code implementations17 Jul 2022 Yinghui Li, Shulin Huang, Xinwei Zhang, Qingyu Zhou, Yangning Li, Ruiyang Liu, Yunbo Cao, Hai-Tao Zheng, Ying Shen

A non-negligible shortcoming of the pre-defined context patterns is that they cannot be flexibly generalized to all kinds of semantic classes, and we call this phenomenon as "semantic sensitivity".

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

1 code implementation 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.

Natural Language Processing

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 Language Modelling +3

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

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 +2

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

4 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 Few-shot NER +2

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.

Saliency Detection Text Generation

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 Natural Language Processing

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

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

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 +1

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 Extraction

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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