Search Results for author: Jianping Shen

Found 20 papers, 1 papers with code

A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification

no code implementations24 Sep 2021 Guang Liu, Hailong Huang, Yuzhao Mao, Weiguo Gao, Xuan Li, Jianping Shen

Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.

Data Augmentation Language Modelling

FPAI at SemEval-2021 Task 6: BERT-MRC for Propaganda Techniques Detection

no code implementations SEMEVAL 2021 Xiaolong Hou, Junsong Ren, Gang Rao, Lianxin Lian, Zhihao Ruan, Yang Mo, Jianping Shen

The objective of subtask 2 of SemEval-2021 Task 6 is to identify techniques used together with the span(s) of text covered by each technique.

Data Augmentation Question Answering

RefBERT: Compressing BERT by Referencing to Pre-computed Representations

no code implementations11 Jun 2021 Xinyi Wang, Haiqin Yang, Liang Zhao, Yang Mo, Jianping Shen

Differently, in this paper, we propose RefBERT to leverage the knowledge learned from the teacher, i. e., facilitating the pre-computed BERT representation on the reference sample and compressing BERT into a smaller student model.

Knowledge Distillation Natural Language Processing

Progressive Open-Domain Response Generation with Multiple Controllable Attributes

no code implementations7 Jun 2021 Haiqin Yang, Xiaoyuan Yao, Yiqun Duan, Jianping Shen, Jie Zhong, Kun Zhang

More specifically, PHED deploys Conditional Variational AutoEncoder (CVAE) on Transformer to include one aspect of attributes at one stage.

Response Generation

PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation

no code implementations SEMEVAL 2021 Shuyi Xie, Jian Ma, Haiqin Yang, Lianxin Jiang, Yang Mo, Jianping Shen

Second, we construct a new vector on the fine-tuned embeddings from XLM-RoBERTa and feed it to a fully-connected network to output the probability of whether the target word in the context has the same meaning or not.

Data Augmentation TAG

Emotion Dynamics Modeling via BERT

no code implementations15 Apr 2021 Haiqin Yang, Jianping Shen

Emotion dynamics modeling is a significant task in emotion recognition in conversation.

Emotion Recognition in Conversation Representation Learning

Automatic Intent-Slot Induction for Dialogue Systems

no code implementations16 Mar 2021 Zengfeng Zeng, Dan Ma, Haiqin Yang, Zhen Gou, Jianping Shen

Automatically and accurately identifying user intents and filling the associated slots from their spoken language are critical to the success of dialogue systems.

Intent Detection Slot Filling

Mention Extraction and Linking for SQL Query Generation

no code implementations EMNLP 2020 Jianqiang Ma, Zeyu Yan, Shuai Pang, Yang Zhang, Jianping Shen

On the WikiSQL benchmark, state-of-the-art text-to-SQL systems typically take a slot-filling approach by building several dedicated models for each type of slots.

Slot Filling Text-To-Sql

FASTMATCH: Accelerating the Inference of BERT-based Text Matching

no code implementations COLING 2020 Shuai Pang, Jianqiang Ma, Zeyu Yan, Yang Zhang, Jianping Shen

Recently, pre-trained language models such as BERT have shown state-of-the-art accuracies in text matching.

Text Matching

SQL Generation via Machine Reading Comprehension

1 code implementation COLING 2020 Zeyu Yan, Jianqiang Ma, Yang Zhang, Jianping Shen

Text-to-SQL systems offers natural language interfaces to databases, which can automatically generates SQL queries given natural language questions.

Machine Reading Comprehension Question Answering +2

Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model

no code implementations Findings of the Association for Computational Linguistics 2020 Bingfeng Luo, Zuo Bai, Kunfeng Lai, Jianping Shen

In addition, it reduces human involvement in template design by using a text stitch model to automatically stitch adjacent template units, which is a step that usually requires careful template design and limits template reusability.

Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion

no code implementations3 Mar 2020 Jingyuan Yang, Guang Liu, Yuzhao Mao, Zhiwei Zhao, Weiguo Gao, Xuan Li, Haiqin Yang, Jianping Shen

Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings.

Cannot find the paper you are looking for? You can Submit a new open access paper.