Search Results for author: Yantao Jia

Found 18 papers, 6 papers with code

Scene Restoring for Narrative Machine Reading Comprehension

no code implementations EMNLP 2020 Zhixing Tian, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yantao Jia, Zhicheng Sheng

Inspired by this behavior of humans, we propose a method to let the machine imagine a scene during reading narrative for better comprehension.

Cloze Test Machine Reading Comprehension +1

FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction

no code implementations EMNLP 2020 Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, Weijian Sun

In this paper, we propose a privacy-preserving medical relation extraction model based on federated learning, which enables training a central model with no single piece of private local data being shared or exchanged.

Federated Learning Knowledge Distillation +2

KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models

no code implementations28 Feb 2022 Daniel Gao, Yantao Jia, Lei LI, Chengzhen Fu, Zhicheng Dou, Hao Jiang, Xinyu Zhang, Lei Chen, Zhao Cao

However, to figure out whether PLMs can be reliable knowledge sources and used as alternative knowledge bases (KBs), we need to further explore some critical features of PLMs.

Model Compression

Towards More Effective and Economic Sparsely-Activated Model

no code implementations14 Oct 2021 Hao Jiang, Ke Zhan, Jianwei Qu, Yongkang Wu, Zhaoye Fei, Xinyu Zhang, Lei Chen, Zhicheng Dou, Xipeng Qiu, Zikai Guo, Ruofei Lai, Jiawen Wu, Enrui Hu, Yinxia Zhang, Yantao Jia, Fan Yu, Zhao Cao

To increase the number of activated experts without an increase in computational cost, we propose SAM (Switch and Mixture) routing, an efficient hierarchical routing mechanism that activates multiple experts in a same device (GPU).

YES SIR!Optimizing Semantic Space of Negatives with Self-Involvement Ranker

no code implementations14 Sep 2021 Ruizhi Pu, Xinyu Zhang, Ruofei Lai, Zikai Guo, Yinxia Zhang, Hao Jiang, Yongkang Wu, Yantao Jia, Zhicheng Dou, Zhao Cao

Finally, supervisory signal in rear compressor is computed based on condition probability and thus can control sample dynamic and further enhance the model performance.

Document Ranking Information Retrieval

Answer Complex Questions: Path Ranker Is All You Need

1 code implementation Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval 2021 Xinyu Zhang, Ke Zhan, Enrui Hu, Chengzhen Fu, Lan Luo, Hao Jiang, Yantao Jia, Fan Yu, Zhicheng Dou, Zhao Cao, Lei Chen

Currently, the most popular method for open-domain Question Answering (QA) adopts "Retriever and Reader" pipeline, where the retriever extracts a list of candidate documents from a large set of documents followed by a ranker to rank the most relevant documents and the reader extracts answer from the candidates.

Open-Domain Question Answering

Emotion Eliciting Machine: Emotion Eliciting Conversation Generation based on Dual Generator

no code implementations18 May 2021 Hao Jiang, Yutao Zhu, Xinyu Zhang, Zhicheng Dou, Pan Du, Te Pi, Yantao Jia

Then we propose a dual encoder-decoder structure to model the generation of responses in both positive and negative side based on the changes of the user's emotion status in the conversation.

OntoZSL: Ontology-enhanced Zero-shot Learning

1 code implementation15 Feb 2021 Yuxia Geng, Jiaoyan Chen, Zhuo Chen, Jeff Z. Pan, Zhiquan Ye, Zonggang Yuan, Yantao Jia, Huajun Chen

The key of implementing ZSL is to leverage the prior knowledge of classes which builds the semantic relationship between classes and enables the transfer of the learned models (e. g., features) from training classes (i. e., seen classes) to unseen classes.

Image Classification Knowledge Graph Completion +2

Towards Robust Textual Representations with Disentangled Contrastive Learning

no code implementations1 Jan 2021 Ningyu Zhang, Xiang Chen, Xin Xie, Shumin Deng, Yantao Jia, Zonggang Yuan, Huajun Chen

Although the self-supervised pre-training of transformer models has resulted in the revolutionizing of natural language processing (NLP) applications and the achievement of state-of-the-art results with regard to various benchmarks, this process is still vulnerable to small and imperceptible permutations originating from legitimate inputs.

Contrastive Learning

FedE: Embedding Knowledge Graphs in Federated Setting

2 code implementations24 Oct 2020 Mingyang Chen, Wen Zhang, Zonggang Yuan, Yantao Jia, Huajun Chen

Knowledge graphs (KGs) consisting of triples are always incomplete, so it's important to do Knowledge Graph Completion (KGC) by predicting missing triples.

Knowledge Graph Completion Knowledge Graph Embedding +1

The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling Analysis

1 code implementation15 Sep 2020 Haiyang Yu, Ningyu Zhang, Shumin Deng, Zonggang Yuan, Yantao Jia, Huajun Chen

Long-tailed relation classification is a challenging problem as the head classes may dominate the training phase, thereby leading to the deterioration of the tail performance.

General Classification Relation Classification

Generative Adversarial Zero-shot Learning via Knowledge Graphs

no code implementations7 Apr 2020 Yuxia Geng, Jiaoyan Chen, Zhuo Chen, Zhiquan Ye, Zonggang Yuan, Yantao Jia, Huajun Chen

However, the side information of classes used now is limited to text descriptions and attribute annotations, which are in short of semantics of the classes.

Image Classification Knowledge Graphs +1

Jointly Modeling Hierarchical and Horizontal Features for Relational Triple Extraction

no code implementations23 Aug 2019 Zhepei Wei, Yantao Jia, Yuan Tian, Mohammad Javad Hosseini, Sujian Li, Mark Steedman, Yi Chang

In this work, we first introduce the hierarchical dependency and horizontal commonality between the two levels, and then propose an entity-enhanced dual tagging framework that enables the triple extraction (TE) task to utilize such interactions with self-learned entity features through an auxiliary entity extraction (EE) task, without breaking the joint decoding of relational triples.

Entity Extraction using GAN graph construction +2

Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms

1 code implementation EMNLP 2018 Yubo Chen, Hang Yang, Kang Liu, Jun Zhao, Yantao Jia

Traditional approaches to the task of ACE event detection primarily regard multiple events in one sentence as independent ones and recognize them separately by using sentence-level information.

Event Detection

Path-Based Attention Neural Model for Fine-Grained Entity Typing

no code implementations29 Oct 2017 Denghui Zhang, Pengshan Cai, Yantao Jia, Manling Li, Yuanzhuo Wang, Xue-Qi Cheng

Fine-grained entity typing aims to assign entity mentions in the free text with types arranged in a hierarchical structure.

Entity Typing

Efficient Parallel Translating Embedding For Knowledge Graphs

1 code implementation30 Mar 2017 Denghui Zhang, Manling Li, Yantao Jia, Yuanzhuo Wang, Xue-Qi Cheng

Knowledge graph embedding aims to embed entities and relations of knowledge graphs into low-dimensional vector spaces.

Knowledge Graph Embedding Knowledge Graphs +2

Locally Adaptive Translation for Knowledge Graph Embedding

no code implementations4 Dec 2015 Yantao Jia, Yuanzhuo Wang, Hailun Lin, Xiaolong Jin, Xue-Qi Cheng

Knowledge graph embedding aims to represent entities and relations in a large-scale knowledge graph as elements in a continuous vector space.

Knowledge Graph Embedding Knowledge Graphs +1

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