Search Results for author: Jinchao Zhang

Found 42 papers, 21 papers with code

Constructing Emotional Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation

no code implementations Findings (EMNLP) 2021 Lei Shen, Jinchao Zhang, Jiao Ou, Xiaofang Zhao, Jie zhou

To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotional consensus and utilize some external unpaired data.

Dialogue Generation

Rephrasing the Reference for Non-Autoregressive Machine Translation

no code implementations30 Nov 2022 Chenze Shao, Jinchao Zhang, Jie zhou, Yang Feng

In response to this problem, we introduce a rephraser to provide a better training target for NAT by rephrasing the reference sentence according to the NAT output.

Machine Translation Sentence +1

AutoCAD: Automatically Generating Counterfactuals for Mitigating Shortcut Learning

1 code implementation29 Nov 2022 Jiaxin Wen, Yeshuang Zhu, Jinchao Zhang, Jie zhou, Minlie Huang

Recent studies have shown the impressive efficacy of counterfactually augmented data (CAD) for reducing NLU models' reliance on spurious features and improving their generalizability.

Counterfactual Data Augmentation via Perspective Transition for Open-Domain Dialogues

1 code implementation30 Oct 2022 Jiao Ou, Jinchao Zhang, Yang Feng, Jie zhou

The dialogue data admits a wide variety of responses for a given dialogue history, especially responses with different semantics.

counterfactual Counterfactual Inference +1

Selecting Stickers in Open-Domain Dialogue through Multitask Learning

1 code implementation Findings (ACL) 2022 Zhexin Zhang, Yeshuang Zhu, Zhengcong Fei, Jinchao Zhang, Jie zhou

With the increasing popularity of online chatting, stickers are becoming important in our online communication.

Mental Health Assessment for the Chatbots

no code implementations14 Jan 2022 Yong Shan, Jinchao Zhang, Zekang Li, Yang Feng, Jie zhou

Previous researches on dialogue system assessment usually focus on the quality evaluation (e. g. fluency, relevance, etc) of responses generated by the chatbots, which are local and technical metrics.

Chatbot

Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation

no code implementations16 Sep 2021 Lei Shen, Jinchao Zhang, Jiao Ou, Xiaofang Zhao, Jie zhou

To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotion consensus and utilize some external unpaired data.

Dialogue Generation

Structure-Enhanced Pop Music Generation via Harmony-Aware Learning

1 code implementation14 Sep 2021 Xueyao Zhang, Jinchao Zhang, Yao Qiu, Li Wang, Jie zhou

Experimental results reveal that compared to the existing methods, HAT owns a much better understanding of the structure and it can also improve the quality of generated music, especially in the form and texture.

Music Generation

Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks

no code implementations EMNLP 2021 Yao Qiu, Jinchao Zhang, Jie zhou

Loading models pre-trained on the large-scale corpus in the general domain and fine-tuning them on specific downstream tasks is gradually becoming a paradigm in Natural Language Processing.

Domain Adaptation Language Modelling

Challenging Instances are Worth Learning: Generating Valuable Negative Samples for Response Selection Training

no code implementations14 Sep 2021 Yao Qiu, Jinchao Zhang, Huiying Ren, Jie zhou

In this way, our negative instances are fluent, context-related, and more challenging for the model to learn, while can not be positive.

Chatbot Retrieval

Guiding Topic Flows in the Generative Chatbot by Enhancing the ConceptNet with the Conversation Corpora

no code implementations12 Sep 2021 Pengda Si, Yao Qiu, Jinchao Zhang, Yujiu Yang

Further analysis individually proves the effectiveness of the enhanced concept graph and the Edge-Transformer architecture.

Chatbot World Knowledge

Towards Expressive Communication with Internet Memes: A New Multimodal Conversation Dataset and Benchmark

1 code implementation4 Sep 2021 Zhengcong Fei, Zekang Li, Jinchao Zhang, Yang Feng, Jie zhou

Compared to previous dialogue tasks, MOD is much more challenging since it requires the model to understand the multimodal elements as well as the emotions behind them.

Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification

1 code implementation EMNLP 2021 Shuhuai Ren, Jinchao Zhang, Lei LI, Xu sun, Jie zhou

Data augmentation aims to enrich training samples for alleviating the overfitting issue in low-resource or class-imbalanced situations.

Bayesian Optimization Data Augmentation +2

Sequence-Level Training for Non-Autoregressive Neural Machine Translation

1 code implementation CL (ACL) 2021 Chenze Shao, Yang Feng, Jinchao Zhang, Fandong Meng, Jie zhou

Non-Autoregressive Neural Machine Translation (NAT) removes the autoregressive mechanism and achieves significant decoding speedup through generating target words independently and simultaneously.

Machine Translation NMT +2

GTM: A Generative Triple-Wise Model for Conversational Question Generation

no code implementations ACL 2021 Lei Shen, Fandong Meng, Jinchao Zhang, Yang Feng, Jie zhou

Generating some appealing questions in open-domain conversations is an effective way to improve human-machine interactions and lead the topic to a broader or deeper direction.

Question Generation Question-Generation

Addressing Inquiries about History: An Efficient and Practical Framework for Evaluating Open-domain Chatbot Consistency

1 code implementation Findings (ACL) 2021 Zekang Li, Jinchao Zhang, Zhengcong Fei, Yang Feng, Jie zhou

Employing human judges to interact with chatbots on purpose to check their capacities is costly and low-efficient, and difficult to get rid of subjective bias.

Chatbot Natural Language Inference

Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances

1 code implementation ACL 2021 Zekang Li, Jinchao Zhang, Zhengcong Fei, Yang Feng, Jie zhou

Nowadays, open-domain dialogue models can generate acceptable responses according to the historical context based on the large-scale pre-trained language models.

Dialogue Evaluation Dialogue Generation

WeChat AI & ICT's Submission for DSTC9 Interactive Dialogue Evaluation Track

no code implementations20 Jan 2021 Zekang Li, Zongjia Li, Jinchao Zhang, Yang Feng, Jie zhou

We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2 (Interactive Dialogue).

Dialogue Evaluation Language Modelling +1

One Comment from One Perspective: An Effective Strategy for Enhancing Automatic Music Comment

1 code implementation COLING 2020 Tengfei Huo, Zhiqiang Liu, Jinchao Zhang, Jie zhou

The automatic generation of music comments is of great significance for increasing the popularity of music and the music platform{'}s activity.

Comment Generation

Token-level Adaptive Training for Neural Machine Translation

1 code implementation EMNLP 2020 Shuhao Gu, Jinchao Zhang, Fandong Meng, Yang Feng, Wanying Xie, Jie zhou, Dong Yu

The vanilla NMT model usually adopts trivial equal-weighted objectives for target tokens with different frequencies and tends to generate more high-frequency tokens and less low-frequency tokens compared with the golden token distribution.

Machine Translation NMT +1

Modeling Inter-Aspect Dependencies with a Non-temporal Mechanism for Aspect-Based Sentiment Analysis

no code implementations12 Aug 2020 Yunlong Liang, Fandong Meng, Jinchao Zhang, Yufeng Chen, Jinan Xu, Jie zhou

For multiple aspects scenario of aspect-based sentiment analysis (ABSA), existing approaches typically ignore inter-aspect relations or rely on temporal dependencies to process aspect-aware representations of all aspects in a sentence.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

Towards Multimodal Response Generation with Exemplar Augmentation and Curriculum Optimization

no code implementations26 Apr 2020 Zeyang Lei, Zekang Li, Jinchao Zhang, Fandong Meng, Yang Feng, Yujiu Yang, Cheng Niu, Jie zhou

Furthermore, to facilitate the convergence of Gaussian mixture prior and posterior distributions, we devise a curriculum optimization strategy to progressively train the model under multiple training criteria from easy to hard.

Response Generation

An Iterative Multi-Knowledge Transfer Network for Aspect-Based Sentiment Analysis

2 code implementations Findings (EMNLP) 2021 Yunlong Liang, Fandong Meng, Jinchao Zhang, Yufeng Chen, Jinan Xu, Jie zhou

Aspect-based sentiment analysis (ABSA) mainly involves three subtasks: aspect term extraction, opinion term extraction, and aspect-level sentiment classification, which are typically handled in a separate or joint manner.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3

A Dependency Syntactic Knowledge Augmented Interactive Architecture for End-to-End Aspect-based Sentiment Analysis

3 code implementations4 Apr 2020 Yunlong Liang, Fandong Meng, Jinchao Zhang, Jinan Xu, Yufeng Chen, Jie zhou

The aspect-based sentiment analysis (ABSA) task remains to be a long-standing challenge, which aims to extract the aspect term and then identify its sentiment orientation. In previous approaches, the explicit syntactic structure of a sentence, which reflects the syntax properties of natural language and hence is intuitively crucial for aspect term extraction and sentiment recognition, is typically neglected or insufficiently modeled.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3

Bridging Text and Video: A Universal Multimodal Transformer for Video-Audio Scene-Aware Dialog

1 code implementation1 Feb 2020 Zekang Li, Zongjia Li, Jinchao Zhang, Yang Feng, Cheng Niu, Jie zhou

Audio-Visual Scene-Aware Dialog (AVSD) is a task to generate responses when chatting about a given video, which is organized as a track of the 8th Dialog System Technology Challenge (DSTC8).

Dialogue Generation Multi-Task Learning

Minimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation

1 code implementation21 Nov 2019 Chenze Shao, Jinchao Zhang, Yang Feng, Fandong Meng, Jie zhou

Non-Autoregressive Neural Machine Translation (NAT) achieves significant decoding speedup through generating target words independently and simultaneously.

Machine Translation Sentence +1

Improving Bidirectional Decoding with Dynamic Target Semantics in Neural Machine Translation

no code implementations5 Nov 2019 Yong Shan, Yang Feng, Jinchao Zhang, Fandong Meng, Wen Zhang

Generally, Neural Machine Translation models generate target words in a left-to-right (L2R) manner and fail to exploit any future (right) semantics information, which usually produces an unbalanced translation.

Machine Translation Translation

CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding

2 code implementations IJCNLP 2019 Yijin Liu, Fandong Meng, Jinchao Zhang, Jie zhou, Yufeng Chen, Jinan Xu

Spoken Language Understanding (SLU) mainly involves two tasks, intent detection and slot filling, which are generally modeled jointly in existing works.

Intent Detection slot-filling +2

A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis

1 code implementation IJCNLP 2019 Yunlong Liang, Fandong Meng, Jinchao Zhang, Jinan Xu, Yufeng Chen, Jie zhou

Aspect based sentiment analysis (ABSA) aims to identify the sentiment polarity towards the given aspect in a sentence, while previous models typically exploit an aspect-independent (weakly associative) encoder for sentence representation generation.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation

3 code implementations ACL 2019 Chenze Shao, Yang Feng, Jinchao Zhang, Fandong Meng, Xilin Chen, Jie zhou

Non-Autoregressive Transformer (NAT) aims to accelerate the Transformer model through discarding the autoregressive mechanism and generating target words independently, which fails to exploit the target sequential information.

Machine Translation Sentence +1

GCDT: A Global Context Enhanced Deep Transition Architecture for Sequence Labeling

1 code implementation ACL 2019 Yijin Liu, Fandong Meng, Jinchao Zhang, Jinan Xu, Yufeng Chen, Jie zhou

Current state-of-the-art systems for sequence labeling are typically based on the family of Recurrent Neural Networks (RNNs).

Ranked #17 on Named Entity Recognition (NER) on CoNLL 2003 (English) (using extra training data)

Chunking NER +2

An end-to-end Neural Network Framework for Text Clustering

no code implementations22 Mar 2019 Jie Zhou, Xingyi Cheng, Jinchao Zhang

Conventional \mbox{methods} generally treat this task using separated steps, including text representation learning and clustering the representations.

Clustering Representation Learning +3

DTMT: A Novel Deep Transition Architecture for Neural Machine Translation

1 code implementation19 Dec 2018 Fandong Meng, Jinchao Zhang

In this paper, we further enhance the RNN-based NMT through increasing the transition depth between consecutive hidden states and build a novel Deep Transition RNN-based Architecture for Neural Machine Translation, named DTMT.

Machine Translation NMT +1

Incorporating Word Reordering Knowledge into Attention-based Neural Machine Translation

no code implementations ACL 2017 Jinchao Zhang, Mingxuan Wang, Qun Liu, Jie zhou

This paper proposes three distortion models to explicitly incorporate the word reordering knowledge into attention-based Neural Machine Translation (NMT) for further improving translation performance.

Machine Translation NMT +2

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