Search Results for author: Liping Jing

Found 21 papers, 9 papers with code

Pairwise Instance Relation Augmentation for Long-tailed Multi-label Text Classification

no code implementations19 Nov 2022 Lin Xiao, Pengyu Xu, Liping Jing, Xiangliang Zhang

In response, we propose a Pairwise Instance Relation Augmentation Network (PIRAN) to augment tailed-label documents for balancing tail labels and head labels.

Multi Label Text Classification Multi-Label Text Classification +1

Approximate better, Attack stronger: Adversarial Example Generation via Asymptotically Gaussian Mixture Distribution

no code implementations24 Sep 2022 Zhengwei Fang, Rui Wang, Tao Huang, Liping Jing

In this paper, we propose Multiple Asymptotically Normal Distribution Attacks (MultiANDA), a novel method that explicitly characterizes adversarial perturbations from a learned distribution.

Adversarial Attack

Divert More Attention to Vision-Language Tracking

1 code implementation3 Jul 2022 Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing

By revealing the potential of VL representation, we expect the community to divert more attention to VL tracking and hope to open more possibilities for future tracking beyond Transformer.

Object Tracking

Hyperbolic Relevance Matching for Neural Keyphrase Extraction

1 code implementation NAACL 2022 Mingyang Song, Yi Feng, Liping Jing

Meanwhile, considering the hierarchical structure hidden in the document, HyperMatch embeds both phrases and documents in the same hyperbolic space via a hyperbolic phrase encoder and a hyperbolic document encoder.

Information Retrieval Keyphrase Extraction +2

Learning Target-aware Representation for Visual Tracking via Informative Interactions

no code implementations7 Jan 2022 Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing, Yilin Lyu, Bing Li, Weiming Hu

The proposed GIM module and InBN mechanism are general and applicable to different backbone types including CNN and Transformer for improvements, as evidenced by our extensive experiments on multiple benchmarks.

Representation Learning Visual Tracking

Topic-Aware Encoding for Extractive Summarization

no code implementations17 Dec 2021 Mingyang Song, Liping Jing

Specifically, a neural topic model is added in the neural-based sentence-level representation learning to adequately consider the central topic information for capturing the critical content in the original document.

Document Summarization Extractive Summarization +1

Reinforced Abstractive Summarization with Adaptive Length Controlling

no code implementations14 Dec 2021 Mingyang Song, Yi Feng, Liping Jing

Document summarization, as a fundamental task in natural language generation, aims to generate a short and coherent summary for a given document.

Abstractive Text Summarization Document Summarization +2

Reinforcing Semantic-Symmetry for Document Summarization

no code implementations14 Dec 2021 Mingyang Song, Liping Jing

Among them, the extractor identifies the salient sentences from the input document, and the abstractor generates a summary from the salient sentences.

Document Summarization reinforcement-learning +2

Importance Estimation from Multiple Perspectives for Keyphrase Extraction

no code implementations EMNLP 2021 Mingyang Song, Liping Jing, Lin Xiao

Keyphrase extraction is a fundamental task in Natural Language Processing, which usually contains two main parts: candidate keyphrase extraction and keyphrase importance estimation.

Chunking Keyphrase Extraction +1

StereoRel: Relational Triple Extraction from a Stereoscopic Perspective

no code implementations ACL 2021 Xuetao Tian, Liping Jing, Lu He, Feng Liu

Relational triple extraction is critical to understanding massive text corpora and constructing large-scale knowledge graph, which has attracted increasing research interest.

Cluster-Wise Hierarchical Generative Model for Deep Amortized Clustering

no code implementations CVPR 2021 Huafeng Liu, Jiaqi Wang, Liping Jing

In this paper, we propose Cluster-wise Hierarchical Generative Model for deep amortized clustering (CHiGac).

Probing BERT in Hyperbolic Spaces

1 code implementation ICLR 2021 Boli Chen, Yao Fu, Guangwei Xu, Pengjun Xie, Chuanqi Tan, Mosha Chen, Liping Jing

We introduce a Poincare probe, a structural probe projecting these embeddings into a Poincare subspace with explicitly defined hierarchies.

Word Embeddings

Does Head Label Help for Long-Tailed Multi-Label Text Classification

1 code implementation24 Jan 2021 Lin Xiao, Xiangliang Zhang, Liping Jing, Chi Huang, Mingyang Song

To address the challenge of insufficient training data on tail label classification, we propose a Head-to-Tail Network (HTTN) to transfer the meta-knowledge from the data-rich head labels to data-poor tail labels.

General Classification Multi Label Text Classification +2

Interpretable Image Recognition by Constructing Transparent Embedding Space

1 code implementation ICCV 2021 Jiaqi Wang, Huafeng Liu, Xinyue Wang, Liping Jing

This plug-in embedding space is spanned by transparent basis concepts which are constructed on the Grassmann manifold.

Hyperbolic Capsule Networks for Multi-Label Classification

no code implementations ACL 2020 Boli Chen, Xin Huang, Lin Xiao, Liping Jing

Second, Hyperbolic Dynamic Routing (HDR) is introduced to aggregate hyperbolic capsules in a label-aware manner, so that the label-level discriminative information can be preserved along the depth of neural networks.

Classification General Classification +1

Cross-Task Transfer for Geotagged Audiovisual Aerial Scene Recognition

1 code implementation ECCV 2020 Di Hu, Xuhong LI, Lichao Mou, Pu Jin, Dong Chen, Liping Jing, Xiaoxiang Zhu, Dejing Dou

With the help of this dataset, we evaluate three proposed approaches for transferring the sound event knowledge to the aerial scene recognition task in a multimodal learning framework, and show the benefit of exploiting the audio information for the aerial scene recognition.

Scene Recognition

Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

1 code implementation26 May 2019 Boli Chen, Xin Huang, Lin Xiao, Zixin Cai, Liping Jing

The main reason is that the tree-likeness of the hyperbolic space matches the complexity of symbolic data with hierarchical structures.

Classification General Classification +1

The Automatic Identification of Butterfly Species

no code implementations18 Mar 2018 Juanying Xie, Qi Hou, Yinghuan Shi, Lv Peng, Liping Jing, Fuzhen Zhuang, Junping Zhang, Xiaoyang Tang, Shengquan Xu

We delete those species with only one living environment image from data set, then partition the rest images from living environment into two subsets, one used as test subset, the other as training subset respectively combined with all standard pattern butterfly images or the standard pattern butterfly images with the same species of the images from living environment.

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