Search Results for author: Wenliang Chen

Found 33 papers, 12 papers with code

MoPE: Mixture of Prefix Experts for Zero-Shot Dialogue State Tracking

1 code implementation12 Apr 2024 Tianwen Tang, Tong Zhu, Haodong Liu, Yin Bai, Jia Cheng, Wenliang Chen

Zero-shot dialogue state tracking (DST) transfers knowledge to unseen domains, reducing the cost of annotating new datasets.

DiffusionDialog: A Diffusion Model for Diverse Dialog Generation with Latent Space

no code implementations10 Apr 2024 Jianxiang Xiang, Zhenhua Liu, Haodong Liu, Yin Bai, Jia Cheng, Wenliang Chen

Previous studies attempted to introduce discrete or Gaussian-based continuous latent variables to address the one-to-many problem, but the diversity is limited.

Denoising Dialogue Generation

Controllable and Diverse Data Augmentation with Large Language Model for Low-Resource Open-Domain Dialogue Generation

no code implementations30 Mar 2024 Zhenhua Liu, Tong Zhu, Jianxiang Xiang, Wenliang Chen

To evaluate the efficacy of data augmentation methods for open-domain dialogue, we designed a clustering-based metric to characterize the semantic diversity of the augmented dialogue data.

Data Augmentation Dialogue Generation +2

Mirror: A Universal Framework for Various Information Extraction Tasks

1 code implementation9 Nov 2023 Tong Zhu, Junfei Ren, Zijian Yu, Mengsong Wu, Guoliang Zhang, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Min Zhang

Sharing knowledge between information extraction tasks has always been a challenge due to the diverse data formats and task variations.

Machine Reading Comprehension

OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch

1 code implementation19 Sep 2023 Juntao Li, Zecheng Tang, Yuyang Ding, Pinzheng Wang, Pei Guo, Wangjie You, Dan Qiao, Wenliang Chen, Guohong Fu, Qiaoming Zhu, Guodong Zhou, Min Zhang

This report provides the main details to pre-train an analogous model, including pre-training data processing, Bilingual Flan data collection, the empirical observations that inspire our model architecture design, training objectives of different stages, and other enhancement techniques.

CED: Catalog Extraction from Documents

1 code implementation28 Apr 2023 Tong Zhu, Guoliang Zhang, Zechang Li, Zijian Yu, Junfei Ren, Mengsong Wu, Zhefeng Wang, Baoxing Huai, Pingfu Chao, Wenliang Chen

To address this problem, we build a large manually annotated corpus, which is the first dataset for the Catalog Extraction from Documents (CED) task.

Catalog Extraction Sentence

SelfMix: Robust Learning Against Textual Label Noise with Self-Mixup Training

1 code implementation COLING 2022 Dan Qiao, Chenchen Dai, Yuyang Ding, Juntao Li, Qiang Chen, Wenliang Chen, Min Zhang

The conventional success of textual classification relies on annotated data, and the new paradigm of pre-trained language models (PLMs) still requires a few labeled data for downstream tasks.

text-classification Text Classification

STAD: Self-Training with Ambiguous Data for Low-Resource Relation Extraction

1 code implementation COLING 2022 Junjie Yu, Xing Wang, Jiangjiang Zhao, Chunjie Yang, Wenliang Chen

The approach first classifies the auto-annotated instances into two groups: confident instances and uncertain instances, according to the probabilities predicted by a teacher model.

Relation Relation Extraction

Better Query Graph Selection for Knowledge Base Question Answering

no code implementations27 Apr 2022 Yonghui Jia, Wenliang Chen

This paper presents a novel approach based on semantic parsing to improve the performance of Knowledge Base Question Answering (KBQA).

Knowledge Base Question Answering Semantic Parsing

A Method of Query Graph Reranking for Knowledge Base Question Answering

no code implementations27 Apr 2022 Yonghui Jia, Wenliang Chen

This paper presents a novel reranking method to better choose the optimal query graph, a sub-graph of knowledge graph, to retrieve the answer for an input question in Knowledge Base Question Answering (KBQA).

Graph Ranking Knowledge Base Question Answering

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

1 code implementation11 Dec 2021 Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan, Min Zhang

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference.

Document-level Event Extraction Event Extraction

Exploiting Rich Syntax for Better Knowledge Base Question Answering

no code implementations16 Jul 2021 Pengju Zhang, Yonghui Jia, Muhua Zhu, Wenliang Chen, Min Zhang

Previous works for encoding questions mainly focus on the word sequences, but seldom consider the information from syntactic trees. In this paper, we propose an approach to learn syntax-based representations for KBQA.

Knowledge Base Question Answering

Improving Relation Extraction with Relational Paraphrase Sentences

1 code implementation COLING 2020 Junjie Yu, Tong Zhu, Wenliang Chen, Wei zhang, Min Zhang

In this paper, we propose an alternative approach to improve RE systems via enriching diverse expressions by relational paraphrase sentences.

Relation Relation Extraction

Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction

1 code implementation COLING 2020 Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei zhang, Min Zhang

The experimental results show that the ranking lists of the comparison systems on the DS-labelled test data and human-annotated test data are different.

Relation Relation Extraction

Improving Neural Relation Extraction with Positive and Unlabeled Learning

no code implementations28 Nov 2019 Zhengqiu He, Wenliang Chen, Yuyi Wang, Wei zhang, Guanchun Wang, Min Zhang

We present a novel approach to improve the performance of distant supervision relation extraction with Positive and Unlabeled (PU) Learning.

reinforcement-learning Reinforcement Learning (RL) +3

CCKS 2019 Shared Task on Inter-Personal Relationship Extraction

1 code implementation29 Aug 2019 Haitao Wang, Zhengqiu He, Tong Zhu, Hao Shao, Wenliang Chen, Min Zhang

In this paper, we present the task definition, the description of data and the evaluation methodology used during this shared task.

Sentence

SEE: Syntax-aware Entity Embedding for Neural Relation Extraction

no code implementations11 Jan 2018 Zhengqiu He, Wenliang Chen, Zhenghua Li, Meishan Zhang, Wei zhang, Min Zhang

First, we encode the context of entities on a dependency tree as sentence-level entity embedding based on tree-GRU.

Relation Relation Classification +3

Distributed Representations for Building Profiles of Users and Items from Text Reviews

no code implementations COLING 2016 Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang

In this paper, we propose an approach to learn distributed representations of users and items from text comments for recommendation systems.

Collaborative Filtering Decision Making +3

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