Search Results for author: Xinyan Xiao

Found 27 papers, 9 papers with code

Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification

no code implementations EMNLP 2020 Yunjie Ji, Hao liu, Bolei He, Xinyan Xiao, Hua Wu, Yanhua Yu

To this end, we propose a novel Diversified Multiple Instance Learning Network (D-MILN), which is able to achieve aspect-level sentiment classification with only document-level weak supervision.

Document-level General Classification +2

SgSum:Transforming Multi-document Summarization into Sub-graph Selection

no code implementations EMNLP 2021 Moye Chen, Wei Li, Jiachen Liu, Xinyan Xiao, Hua Wu, Haifeng Wang

Comparing with traditional methods, our method has two main advantages: (1) the relations between sentences are captured by modeling both the graph structure of the whole document set and the candidate sub-graphs; (2) directly outputs an integrate summary in the form of sub-graph which is more informative and coherent.

Document Summarization Multi-Document Summarization

Learning with Noisy Correspondence for Cross-modal Matching

no code implementations NeurIPS 2021 Zhenyu Huang, guocheng niu, Xiao Liu, Wenbiao Ding, Xinyan Xiao, Hua Wu, Xi Peng

Based on this observation, we reveal and study a latent and challenging direction in cross-modal matching, named noisy correspondence, which could be regarded as a new paradigm of noisy labels.

Cross-Modal Retrieval Language understanding +1

SgSum: Transforming Multi-document Summarization into Sub-graph Selection

1 code implementation25 Oct 2021 Moye Chen, Wei Li, Jiachen Liu, Xinyan Xiao, Hua Wu, Haifeng Wang

Comparing with traditional methods, our method has two main advantages: (1) the relations between sentences are captured by modeling both the graph structure of the whole document set and the candidate sub-graphs; (2) directly outputs an integrate summary in the form of sub-graph which is more informative and coherent.

Document Summarization Multi-Document Summarization

A Multimodal Sentiment Dataset for Video Recommendation

no code implementations17 Sep 2021 Hongxuan Tang, Hao liu, Xinyan Xiao, Hua Wu

Based on this, we propose a multimodal sentiment analysis dataset, named baiDu Video Sentiment dataset (DuVideoSenti), and introduce a new sentiment system which is designed to describe the sentimental style of a video on recommendation scenery.

Language understanding Multimodal Sentiment Analysis +1

Controllable Dialogue Generation with Disentangled Multi-grained Style Specification and Attribute Consistency Reward

no code implementations14 Sep 2021 Zhe Hu, Zhiwei Cao, Hou Pong Chan, Jiachen Liu, Xinyan Xiao, Jinsong Su, Hua Wu

Controllable text generation is an appealing but challenging task, which allows users to specify particular attributes of the generated outputs.

Dialogue Generation

Fine-grained Entity Typing via Label Reasoning

no code implementations EMNLP 2021 Qing Liu, Hongyu Lin, Xinyan Xiao, Xianpei Han, Le Sun, Hua Wu

Conventional entity typing approaches are based on independent classification paradigms, which make them difficult to recognize inter-dependent, long-tailed and fine-grained entity types.

Entity Typing

DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation

no code implementations30 Aug 2021 Lijie Wang, Hao liu, Shuyuan Peng, Hongxuan Tang, Xinyan Xiao, Ying Chen, Hua Wu, Haifeng Wang

Therefore, in order to systematically evaluate the factors for building trustworthy systems, we propose a novel and well-annotated sentiment analysis dataset to evaluate robustness and interpretability.

Sentiment Analysis

BASS: Boosting Abstractive Summarization with Unified Semantic Graph

no code implementations ACL 2021 Wenhao Wu, Wei Li, Xinyan Xiao, Jiachen Liu, Ziqiang Cao, Sujian Li, Hua Wu, Haifeng Wang

Abstractive summarization for long-document or multi-document remains challenging for the Seq2Seq architecture, as Seq2Seq is not good at analyzing long-distance relations in text.

Abstractive Text Summarization Document Summarization +1

A Practical Chinese Dependency Parser Based on A Large-scale Dataset

2 code implementations2 Sep 2020 Shuai Zhang, Lijie Wang, Ke Sun, Xinyan Xiao

DDParser is extended on the graph-based biaffine parser to accommodate to the characteristics of Chinese dataset.

Dependency Parsing

Leveraging Graph to Improve Abstractive Multi-Document Summarization

1 code implementation ACL 2020 Wei Li, Xinyan Xiao, Jiachen Liu, Hua Wu, Haifeng Wang, Junping Du

Graphs that capture relations between textual units have great benefits for detecting salient information from multiple documents and generating overall coherent summaries.

Document Summarization Multi-Document Summarization

SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis

4 code implementations ACL 2020 Hao Tian, Can Gao, Xinyan Xiao, Hao liu, Bolei He, Hua Wu, Haifeng Wang, Feng Wu

In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair.

Multi-Label Classification Sentiment Analysis

Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer

1 code implementation ACL 2020 Chulun Zhou, Liang-Yu Chen, Jiachen Liu, Xinyan Xiao, Jinsong Su, Sheng Guo, Hua Wu

Unsupervised style transfer aims to change the style of an input sentence while preserving its original content without using parallel training data.

Denoising Style Transfer

Enhancing Local Feature Extraction with Global Representation for Neural Text Classification

no code implementations IJCNLP 2019 Guocheng Niu, Hengru Xu, Bolei He, Xinyan Xiao, Hua Wu, Sheng Gao

For text classification, traditional local feature driven models learn long dependency by deeply stacking or hybrid modeling.

Classification General Classification +1

ARNOR: Attention Regularization based Noise Reduction for Distant Supervision Relation Classification

no code implementations ACL 2019 Wei Jia, Dai Dai, Xinyan Xiao, Hua Wu

In this paper, we propose ARNOR, a novel Attention Regularization based NOise Reduction framework for distant supervision relation classification.

Classification General Classification +1

Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension

no code implementations ACL 2018 Zhen Wang, Jiachen Liu, Xinyan Xiao, Yajuan Lyu, Tian Wu

While sophisticated neural-based techniques have been developed in reading comprehension, most approaches model the answer in an independent manner, ignoring its relations with other answer candidates.

Answer Selection Reading Comprehension

DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

3 code implementations WS 2018 Wei He, Kai Liu, Jing Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yu-An Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, Haifeng Wang

Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.

Machine Reading Comprehension

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