Search Results for author: Minlie Huang

Found 109 papers, 52 papers with code

Transferable Persona-Grounded Dialogues via Grounded Minimal Edits

no code implementations16 Sep 2021 Chen Henry Wu, Yinhe Zheng, Xiaoxi Mao, Minlie Huang

Grounded dialogue models generate responses that are grounded on certain concepts.

Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation

no code implementations14 Sep 2021 Chujie Zheng, Minlie Huang

Dialog grounding enables conversational models to make full use of external information to establish multiple desired qualities, such as knowledgeable, engaging and empathetic.

Few-Shot Learning

CEM: Commonsense-aware Empathetic Response Generation

no code implementations13 Sep 2021 Sahand Sabour, Chujie Zheng, Minlie Huang

We evaluate our approach on EmpatheticDialogues, which is a widely-used benchmark dataset for empathetic response generation.

Empathetic Response Generation

PPT: Pre-trained Prompt Tuning for Few-shot Learning

no code implementations9 Sep 2021 Yuxian Gu, Xu Han, Zhiyuan Liu, Minlie Huang

To ensure the generalization of PPT, we formulate similar classification tasks into a unified task form and pre-train soft prompts for this unified task.

Few-Shot Learning

LOT: A Benchmark for Evaluating Chinese Long Text Understanding and Generation

no code implementations30 Aug 2021 Jian Guan, Zhuoer Feng, Yamei Chen, Ruilin He, Xiaoxi Mao, Changjie Fan, Minlie Huang

Therefore, we propose LOT, a benchmark including two understanding and two generation tasks for Chinese long text modeling evaluation.

Text Infilling

Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems

no code implementations28 Aug 2021 Fei Mi, Wanhao Zhou, Fengyu Cai, Lingjing Kong, Minlie Huang, Boi Faltings

In this paper, we devise a self-training approach to utilize the abundant unlabeled dialog data to further improve state-of-the-art pre-trained models in few-shot learning scenarios for ToD systems.

Few-Shot Learning Intent Classification +2

EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training

1 code implementation3 Aug 2021 Hao Zhou, Pei Ke, Zheng Zhang, Yuxian Gu, Yinhe Zheng, Chujie Zheng, Yida Wang, Chen Henry Wu, Hao Sun, Xiaocong Yang, Bosi Wen, Xiaoyan Zhu, Minlie Huang, Jie Tang

Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue data and the model size compared with English ones.

KuiLeiXi: a Chinese Open-Ended Text Adventure Game

no code implementations ACL 2021 Yadong Xi, Xiaoxi Mao, Le Li, Lei Lin, Yanjiang Chen, Shuhan Yang, Xuhan Chen, Kailun Tao, Zhi Li, Gongzheng li, Lin Jiang, Siyan Liu, Zeng Zhao, Minlie Huang, Changjie Fan, Zhipeng Hu

Equipped with GPT-2 and the latest GPT-3, AI Dungeon has been seen as a famous example of the powerful text generation capabilities of large-scale pre-trained language models, and a possibility for future games.

Text Generation

End-to-End Task-Oriented Dialog Modeling with Semi-Structured Knowledge Management

no code implementations22 Jun 2021 Silin Gao, Ryuichi Takanobu, Minlie Huang

In this paper, we formulate a task of modeling TOD grounded on a fusion of structured and unstructured knowledge.

Language Modelling

CPM-2: Large-scale Cost-effective Pre-trained Language Models

1 code implementation20 Jun 2021 Zhengyan Zhang, Yuxian Gu, Xu Han, Shengqi Chen, Chaojun Xiao, Zhenbo Sun, Yuan YAO, Fanchao Qi, Jian Guan, Pei Ke, Yanzheng Cai, Guoyang Zeng, Zhixing Tan, Zhiyuan Liu, Minlie Huang, Wentao Han, Yang Liu, Xiaoyan Zhu, Maosong Sun

We present a suite of cost-effective techniques for the use of PLMs to deal with the efficiency issues of pre-training, fine-tuning, and inference.

JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs

1 code implementation19 Jun 2021 Pei Ke, Haozhe Ji, Yu Ran, Xin Cui, LiWei Wang, Linfeng Song, Xiaoyan Zhu, Minlie Huang

Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which largely ignore the graph structure during encoding and lack elaborate pre-training tasks to explicitly model graph-text alignments.

Graph Reconstruction KG-to-Text Generation +3

A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering

no code implementations ACL 2021 Zhihong Shao, Lifeng Shang, Qun Liu, Minlie Huang

This setting gives rise to the spurious solution problem: there may exist many spurious solutions that coincidentally derive the correct answer, but training on such solutions can hurt model performance (e. g., producing wrong solutions or answers).

Question Answering

Semantic-Enhanced Explainable Finetuning for Open-Domain Dialogues

no code implementations6 Jun 2021 Chen Henry Wu, Yinhe Zheng, Yida Wang, Zhenyu Yang, Minlie Huang

In this paper, we propose to combine pretrained language models with the modular dialogue paradigm for open-domain dialogue modeling.

Language Modelling

NAST: A Non-Autoregressive Generator with Word Alignment for Unsupervised Text Style Transfer

1 code implementation4 Jun 2021 Fei Huang, Zikai Chen, Chen Henry Wu, Qihan Guo, Xiaoyan Zhu, Minlie Huang

First, we observe that most words in the transferred sentence can be aligned with related words in the source sentence, so we explicitly model word alignments to suppress irrelevant words.

Style Transfer Text Style Transfer +2

PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support

1 code implementation3 Jun 2021 Hao Sun, Zhenru Lin, Chujie Zheng, Siyang Liu, Minlie Huang

In this paper, we propose PsyQA, a Chinese dataset of psychological health support in the form of question and answer pair.

Towards Emotional Support Dialog Systems

1 code implementation ACL 2021 Siyang Liu, Chujie Zheng, Orianna Demasi, Sahand Sabour, Yu Li, Zhou Yu, Yong Jiang, Minlie Huang

Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats.

Diversifying Dialog Generation via Adaptive Label Smoothing

1 code implementation ACL 2021 Yida Wang, Yinhe Zheng, Yong Jiang, Minlie Huang

Neural dialogue generation models trained with the one-hot target distribution suffer from the over-confidence issue, which leads to poor generation diversity as widely reported in the literature.

Dialogue Generation

Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence

1 code implementation ACL 2021 Jian Guan, Xiaoxi Mao, Changjie Fan, Zitao Liu, Wenbiao Ding, Minlie Huang

Generating long and coherent text is an important but challenging task, particularly for open-ended language generation tasks such as story generation.

Semantic Similarity Semantic Textual Similarity +1

OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics

1 code implementation ACL 2021 Jian Guan, Zhexin Zhang, Zhuoer Feng, Zitao Liu, Wenbiao Ding, Xiaoxi Mao, Changjie Fan, Minlie Huang

Automatic metrics are essential for developing natural language generation (NLG) models, particularly for open-ended language generation tasks such as story generation.

Text Generation

CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation

1 code implementation18 May 2021 Chujie Zheng, Yong liu, Wei Chen, Yongcai Leng, Minlie Huang

However, existing methods for empathetic response generation usually either consider only one empathy factor or ignore the hierarchical relationships between different factors, leading to a weak ability of empathy modeling.

Empathetic Response Generation Open-Domain Dialog

Stylized Story Generation with Style-Guided Planning

no code implementations18 May 2021 Xiangzhe Kong, Jialiang Huang, Ziquan Tung, Jian Guan, Minlie Huang

Current storytelling systems focus more ongenerating stories with coherent plots regard-less of the narration style, which is impor-tant for controllable text generation.

Text Generation

HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management

1 code implementation13 May 2021 Silin Gao, Ryuichi Takanobu, Wei Peng, Qun Liu, Minlie Huang

To address this task, we propose a TOD system with hybrid knowledge management, HyKnow.

A Text GAN for Language Generation with Non-Autoregressive Generator

no code implementations1 Jan 2021 Fei Huang, Jian Guan, Pei Ke, Qihan Guo, Xiaoyan Zhu, Minlie Huang

Despite the great success of Generative Adversarial Networks (GANs) in generating high-quality images, GANs for text generation still face two major challenges: first, most text GANs are unstable in training mainly due to ineffective optimization of the generator, and they heavily rely on maximum likelihood pretraining; second, most text GANs adopt autoregressive generators without latent variables, which largely limits the ability to learn latent representations for natural language text.

Decipherment Representation Learning +1

Robustness Testing of Language Understanding in Task-Oriented Dialog

2 code implementations ACL 2021 Jiexi Liu, Ryuichi Takanobu, Jiaxin Wen, Dazhen Wan, Hongguang Li, Weiran Nie, Cheng Li, Wei Peng, Minlie Huang

Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.

Data Augmentation Natural Language Understanding

AdvExpander: Generating Natural Language Adversarial Examples by Expanding Text

no code implementations18 Dec 2020 Zhihong Shao, Zitao Liu, Jiyong Zhang, Zhongqin Wu, Minlie Huang

In this paper, we present AdvExpander, a method that crafts new adversarial examples by expanding text, which is complementary to previous substitution-based methods.

Text Matching

ExpanRL: Hierarchical Reinforcement Learning for Course Concept Expansion in MOOCs

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, Minlie Huang, Zhiyuan Liu

Within the prosperity of Massive Open Online Courses (MOOCs), the education applications that automatically provide extracurricular knowledge for MOOC users become rising research topics.

Hierarchical Reinforcement Learning

Reinforced Molecular Optimization with Neighborhood-Controlled Grammars

1 code implementation NeurIPS 2020 Chencheng Xu, Qiao Liu, Minlie Huang, Tao Jiang

A major challenge in the pharmaceutical industry is to design novel molecules with specific desired properties, especially when the property evaluation is costly.

 Ranked #1 on Molecular Graph Generation on ZINC (QED Top-3 metric)

Graph Generation Molecular Graph Generation

CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation

1 code implementation20 Oct 2020 Wenchang Ma, Ryuichi Takanobu, Minlie Huang

Growing interests have been attracted in Conversational Recommender Systems (CRS), which explore user preference through conversational interactions in order to make appropriate recommendation.

Recommendation Systems Text Generation

MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation

4 code implementations12 Oct 2020 Ting Han, Ximing Liu, Ryuichi Takanobu, Yixin Lian, Chongxuan Huang, Dazhen Wan, Wei Peng, Minlie Huang

In this paper, we introduce MultiWOZ 2. 3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset.

Dialogue State Tracking Natural Language Understanding +1

Youling: an AI-assisted Lyrics Creation System

no code implementations EMNLP 2020 Rongsheng Zhang, Xiaoxi Mao, Le Li, Lin Jiang, Lin Chen, Zhiwei Hu, Yadong Xi, Changjie Fan, Minlie Huang

In the lyrics generation process, \textit{Youling} supports traditional one pass full-text generation mode as well as an interactive generation mode, which allows users to select the satisfactory sentences from generated candidates conditioned on preceding context.

Text Generation

Stylized Dialogue Response Generation Using Stylized Unpaired Texts

1 code implementation27 Sep 2020 Yinhe Zheng, Zikai Chen, Rongsheng Zhang, Shilei Huang, Xiaoxi Mao, Minlie Huang

However, this task is far from well-explored due to the difficulties of rendering a particular style in coherent responses, especially when the target style is embedded only in unpaired texts that cannot be directly used to train the dialogue model.

Dialogue Generation

Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph

1 code implementation EMNLP 2020 Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Xiaoyan Zhu, Minlie Huang

Despite the success of generative pre-trained language models on a series of text generation tasks, they still suffer in cases where reasoning over underlying commonsense knowledge is required during generation.

Text Generation

Generating Commonsense Explanation by Extracting Bridge Concepts from Reasoning Paths

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Minlie Huang

Commonsense explanation generation aims to empower the machine's sense-making capability by generating plausible explanations to statements against commonsense.

Dialogue Distillation: Open-Domain Dialogue Augmentation Using Unpaired Data

1 code implementation EMNLP 2020 Rongsheng Zhang, Yinhe Zheng, Jianzhi Shao, Xiaoxi Mao, Yadong Xi, Minlie Huang

Further, a model-level distillation process is employed to distill a teacher model trained on high-quality paired data to augmented dialogue pairs, thereby preventing dialogue models from being affected by the noise in the augmented data.

Data Augmentation

Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation

1 code implementation Findings of the Association for Computational Linguistics 2020 Chujie Zheng, Yunbo Cao, Daxin Jiang, Minlie Huang

In a multi-turn knowledge-grounded dialog, the difference between the knowledge selected at different turns usually provides potential clues to knowledge selection, which has been largely neglected in previous research.

UNION: An Unreferenced Metric for Evaluating Open-ended Story Generation

1 code implementation EMNLP 2020 Jian Guan, Minlie Huang

Experiments on two story datasets demonstrate that UNION is a reliable measure for evaluating the quality of generated stories, which correlates better with human judgments and is more generalizable than existing state-of-the-art metrics.

Text Generation

A Large-Scale Chinese Short-Text Conversation Dataset

1 code implementation10 Aug 2020 Yida Wang, Pei Ke, Yinhe Zheng, Kaili Huang, Yong Jiang, Xiaoyan Zhu, Minlie Huang

The cleaned dataset and the pre-training models will facilitate the research of short-text conversation modeling.

Dialogue Generation Short-Text Conversation

FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data

no code implementations29 Jul 2020 Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei. Lin, Jingren Zhou

Then we instantiate this search strategy by optimizing both a dedicated graph neural network (GNN) and the adjacency tensor associated with the defined feature graph.

Recommendation Systems

Knowledge-Aided Open-Domain Question Answering

1 code implementation9 Jun 2020 Mantong Zhou, Zhouxing Shi, Minlie Huang, Xiaoyan Zhu

During document retrieval, a candidate document is scored by considering its relationship to the question and other documents.

Open-Domain Question Answering Reading Comprehension

Is Your Goal-Oriented Dialog Model Performing Really Well? Empirical Analysis of System-wise Evaluation

no code implementations15 May 2020 Ryuichi Takanobu, Qi Zhu, Jinchao Li, Baolin Peng, Jianfeng Gao, Minlie Huang

There is a growing interest in developing goal-oriented dialog systems which serve users in accomplishing complex tasks through multi-turn conversations.

Goal-Oriented Dialog

A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction

1 code implementation ACL 2020 Yilin Niu, Fangkai Jiao, Mantong Zhou, Ting Yao, Jingfang Xu, Minlie Huang

Neural models have achieved great success on machine reading comprehension (MRC), many of which typically consist of two components: an evidence extractor and an answer predictor.

Machine Reading Comprehension Multi-Choice MRC +1

Learning Goal-oriented Dialogue Policy with Opposite Agent Awareness

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Zheng Zhang, Lizi Liao, Xiaoyan Zhu, Tat-Seng Chua, Zitao Liu, Yan Huang, Minlie Huang

Most existing approaches for goal-oriented dialogue policy learning used reinforcement learning, which focuses on the target agent policy and simply treat the opposite agent policy as part of the environment.

Decision Making

Multi-Agent Task-Oriented Dialog Policy Learning with Role-Aware Reward Decomposition

1 code implementation ACL 2020 Ryuichi Takanobu, Runze Liang, Minlie Huang

To avoid explicitly building a user simulator beforehand, we propose Multi-Agent Dialog Policy Learning, which regards both the system and the user as the dialog agents.

KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation

1 code implementation ACL 2020 Hao Zhou, Chujie Zheng, Kaili Huang, Minlie Huang, Xiaoyan Zhu

The research of knowledge-driven conversational systems is largely limited due to the lack of dialog data which consist of multi-turn conversations on multiple topics and with knowledge annotations.

Domain Adaptation Knowledge Graphs +1

Recent Advances and Challenges in Task-oriented Dialog System

no code implementations17 Mar 2020 Zheng Zhang, Ryuichi Takanobu, Qi Zhu, Minlie Huang, Xiaoyan Zhu

Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

5 code implementations NeurIPS 2020 Kaidi Xu, Zhouxing Shi, huan zhang, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh

Linear relaxation based perturbation analysis (LiRPA) for neural networks, which computes provable linear bounds of output neurons given a certain amount of input perturbation, has become a core component in robustness verification and certified defense.

Quantization

CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset

2 code implementations TACL 2020 Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, Minlie Huang

To advance multi-domain (cross-domain) dialogue modeling as well as alleviate the shortage of Chinese task-oriented datasets, we propose CrossWOZ, the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset.

Dialogue State Tracking Task-Oriented Dialogue Systems

Robustness Verification for Transformers

1 code implementation ICLR 2020 Zhouxing Shi, huan zhang, Kai-Wei Chang, Minlie Huang, Cho-Jui Hsieh

Robustness verification that aims to formally certify the prediction behavior of neural networks has become an important tool for understanding model behavior and obtaining safety guarantees.

Sentiment Analysis

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

1 code implementation ACL 2020 Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang

We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.

Task-Oriented Dialogue Systems

CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation

1 code implementation3 Feb 2020 Fei Huang, Dazhen Wan, Zhihong Shao, Pei Ke, Jian Guan, Yilin Niu, Xiaoyan Zhu, Minlie Huang

In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions.

Text Generation

A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation

1 code implementation TACL 2020 Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, Minlie Huang

To further capture the causal and temporal dependencies between the sentences in a reasonable story, we employ multi-task learning which combines a discriminative objective to distinguish true and fake stories during fine-tuning.

Multi-Task Learning Text Generation

Robust Reading Comprehension with Linguistic Constraints via Posterior Regularization

no code implementations16 Nov 2019 Mantong Zhou, Minlie Huang, Xiaoyan Zhu

In this paper, we address the over-confidence issue and the over-sensitivity issue existing in current RC models simultaneously with the help of external linguistic knowledge.

Machine Reading Comprehension

A Pre-training Based Personalized Dialogue Generation Model with Persona-sparse Data

1 code implementation12 Nov 2019 Yinhe Zheng, Rongsheng Zhang, Xiaoxi Mao, Minlie Huang

Further, to incorporate the target persona in the decoding process and to balance its contribution, an attention routing structure is devised in the decoder to merge features extracted from the target persona and dialogue contexts using dynamically predicted weights.

Dialogue Generation Language Modelling

SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge

1 code implementation EMNLP 2020 Pei Ke, Haozhe Ji, Siyang Liu, Xiaoyan Zhu, Minlie Huang

To benefit the downstream tasks in sentiment analysis, we propose a novel language representation model called SentiLARE, which introduces word-level linguistic knowledge including part-of-speech tag and sentiment polarity (inferred from SentiWordNet) into pre-trained models.

Data Augmentation Language Modelling +2

Out-of-domain Detection for Natural Language Understanding in Dialog Systems

no code implementations9 Sep 2019 Yinhe Zheng, Guanyi Chen, Minlie Huang

Besides, we also demonstrate that the effectiveness of these pseudo OOD data can be further improved by efficiently utilizing unlabeled data.

Natural Language Understanding Text Generation

Robustness to Modification with Shared Words in Paraphrase Identification

no code implementations Findings of the Association for Computational Linguistics 2020 Zhouxing Shi, Minlie Huang

Revealing the robustness issues of natural language processing models and improving their robustness is important to their performance under difficult situations.

Language Modelling Paraphrase Identification

Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog

1 code implementation IJCNLP 2019 Ryuichi Takanobu, Hanlin Zhu, Minlie Huang

Many studies apply Reinforcement Learning to learn a dialog policy with the reward function which requires elaborate design and pre-specified user goals.

ARAML: A Stable Adversarial Training Framework for Text Generation

1 code implementation IJCNLP 2019 Pei Ke, Fei Huang, Minlie Huang, Xiaoyan Zhu

The generator is optimized with maximum likelihood estimation augmented by the discriminator's rewards instead of policy gradient.

Text Generation

Long and Diverse Text Generation with Planning-based Hierarchical Variational Model

1 code implementation IJCNLP 2019 Zhihong Shao, Minlie Huang, Jiangtao Wen, Wenfei Xu, Xiaoyan Zhu

Existing neural methods for data-to-text generation are still struggling to produce long and diverse texts: they are insufficient to model input data dynamically during generation, to capture inter-sentence coherence, or to generate diversified expressions.

Data-to-Text Generation Latent Variable Models

Deep Conversational Recommender in Travel

no code implementations25 Jun 2019 Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua

When traveling to a foreign country, we are often in dire need of an intelligent conversational agent to provide instant and informative responses to our various queries.

Challenges in Building Intelligent Open-domain Dialog Systems

no code implementations13 May 2019 Minlie Huang, Xiaoyan Zhu, Jianfeng Gao

This paper reviews the recent works on neural approaches that are devoted to addressing three challenges in developing such systems: semantics, consistency, and interactiveness.

Open-Domain Dialog

ConvLab: Multi-Domain End-to-End Dialog System Platform

1 code implementation ACL 2019 Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Xiang Li, Yaoqin Zhang, Zheng Zhang, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, Jianfeng Gao

We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments.

Domain-Constrained Advertising Keyword Generation

no code implementations27 Feb 2019 Hao Zhou, Minlie Huang, Yishun Mao, Changlei Zhu, Peng Shu, Xiaoyan Zhu

Second, the inefficient ad impression issue: a large proportion of search queries, which are unpopular yet relevant to many ad keywords, have no ads presented on their search result pages.

Personalized Dialogue Generation with Diversified Traits

3 code implementations28 Jan 2019 Yinhe Zheng, Guanyi Chen, Minlie Huang, Song Liu, Xuan Zhu

In this paper, we investigate the problem of incorporating explicit personality traits in dialogue generation to deliver personalized dialogues.

Dialogue Generation

A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues

1 code implementation1 Dec 2018 Zhouxing Shi, Minlie Huang

This paper presents a deep sequential model for parsing discourse dependency structures of multi-party dialogues.

Discourse Parsing Link Prediction

A Hierarchical Framework for Relation Extraction with Reinforcement Learning

2 code implementations9 Nov 2018 Ryuichi Takanobu, Tianyang Zhang, Jiexi Liu, Minlie Huang

The whole extraction process is decomposed into a hierarchy of two-level RL policies for relation detection and entity extraction respectively, so that it is more feasible and natural to deal with overlapping relations.

Entity Extraction using GAN Hierarchical Reinforcement Learning +1

Word Embedding based Edit Distance

no code implementations25 Oct 2018 Yilin Niu, chao qiao, Hang Li, Minlie Huang

Text similarity calculation is a fundamental problem in natural language processing and related fields.

Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning

no code implementations17 Sep 2018 Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang, Xiaoyan Zhu

The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance.

Multi-agent Reinforcement Learning

Story Ending Generation with Incremental Encoding and Commonsense Knowledge

1 code implementation30 Aug 2018 Jian Guan, Yansen Wang, Minlie Huang

This task requires not only to understand the context clues which play an important role in planning the plot but also to handle implicit knowledge to make a reasonable, coherent story.

Reinforcement Learning for Relation Classification from Noisy Data

2 code implementations24 Aug 2018 Jun Feng, Minlie Huang, Li Zhao, Yang Yang, Xiaoyan Zhu

In this paper, we propose a novel model for relation classification at the sentence level from noisy data.

Classification Relation Classification

An Operation Network for Abstractive Sentence Compression

no code implementations COLING 2018 Naitong Yu, Jie Zhang, Minlie Huang, Xiaoyan Zhu

Delete-based models have the strong ability to delete undesired words, while generate-based models are able to reorder or rephrase the words, which are more coherent to human sentence compression.

Sentence Compression Text Generation

Generating Informative Responses with Controlled Sentence Function

1 code implementation ACL 2018 Pei Ke, Jian Guan, Minlie Huang, Xiaoyan Zhu

Experiments show that our model outperforms state-of-the-art baselines, and it has the ability to generate responses with both controlled sentence function and informative content.

Text Generation

Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders

1 code implementation ACL 2018 Yansen Wang, Chen-Yi Liu, Minlie Huang, Liqiang Nie

Asking good questions in large-scale, open-domain conversational systems is quite significant yet rather untouched.

Question Generation

Memory-augmented Dialogue Management for Task-oriented Dialogue Systems

no code implementations1 May 2018 Zheng Zhang, Minlie Huang, Zhongzhou Zhao, Feng Ji, Haiqing Chen, Xiaoyan Zhu

Dialogue management (DM) decides the next action of a dialogue system according to the current dialogue state, and thus plays a central role in task-oriented dialogue systems.

Dialogue Management Task-Oriented Dialogue Systems

An Interpretable Reasoning Network for Multi-Relation Question Answering

1 code implementation COLING 2018 Mantong Zhou, Minlie Huang, Xiaoyan Zhu

Multi-relation Question Answering is a challenging task, due to the requirement of elaborated analysis on questions and reasoning over multiple fact triples in knowledge base.

Question Answering

Augmenting End-to-End Dialog Systems with Commonsense Knowledge

no code implementations16 Sep 2017 Tom Young, Erik Cambria, Iti Chaturvedi, Minlie Huang, Hao Zhou, Subham Biswas

Building dialog agents that can converse naturally with humans is a challenging yet intriguing problem of artificial intelligence.

Assigning personality/identity to a chatting machine for coherent conversation generation

1 code implementation9 Jun 2017 Qiao Qian, Minlie Huang, Haizhou Zhao, Jingfang Xu, Xiaoyan Zhu

Endowing a chatbot with personality or an identity is quite challenging but critical to deliver more realistic and natural conversations.

Chatbot

Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory

4 code implementations4 Apr 2017 Hao Zhou, Minlie Huang, Tianyang Zhang, Xiaoyan Zhu, Bing Liu

Perception and expression of emotion are key factors to the success of dialogue systems or conversational agents.

GAKE: Graph Aware Knowledge Embedding

1 code implementation COLING 2016 Jun Feng, Minlie Huang, Yang Yang, Xiaoyan Zhu

Knowledge embedding, which projects triples in a given knowledge base to d-dimensional vectors, has attracted considerable research efforts recently.

Context-aware Natural Language Generation for Spoken Dialogue Systems

no code implementations COLING 2016 Hao Zhou, Minlie Huang, Xiaoyan Zhu

Most tranditional QA systems based on templates or rules tend to generate rigid and stylised responses without the natural variation of human language.

Dialogue Generation Question Answering +1

Product Review Summarization by Exploiting Phrase Properties

no code implementations COLING 2016 Naitong Yu, Minlie Huang, Yuanyuan Shi, Xiaoyan Zhu

The main idea of our method is to leverage phrase properties to choose a subset of optimal phrases for generating the final summary.

Abstractive Text Summarization Language Modelling

Linguistically Regularized LSTMs for Sentiment Classification

no code implementations12 Nov 2016 Qiao Qian, Minlie Huang, Jinhao Lei, Xiaoyan Zhu

In this paper, we propose simple models trained with sentence-level annotation, but also attempt to generating linguistically coherent representations by employing regularizers that model the linguistic role of sentiment lexicons, negation words, and intensity words.

Classification General Classification +1

KSR: A Semantic Representation of Knowledge Graph within a Novel Unsupervised Paradigm

no code implementations27 Aug 2016 Han Xiao, Minlie Huang, Xiaoyan Zhu

Since both aspects and categories are semantics-relevant, the collection of categories in each aspect is treated as the semantic representation of this triple.

Entity Retrieval Knowledge Graph Embedding +1

Modeling Rich Contexts for Sentiment Classification with LSTM

no code implementations5 May 2016 Minlie Huang, Yujie Cao, Chao Dong

Sentiment analysis on social media data such as tweets and weibo has become a very important and challenging task.

Classification General Classification +1

SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions

no code implementations17 Apr 2016 Han Xiao, Minlie Huang, Xiaoyan Zhu

To this end, this paper proposes a semantic representation method for knowledge graph \textbf{(KSR)}, which imposes a two-level hierarchical generative process that globally extracts many aspects and then locally assigns a specific category in each aspect for every triple.

Knowledge Graph Embedding Question Answering

From One Point to A Manifold: Knowledge Graph Embedding For Precise Link Prediction

no code implementations15 Dec 2015 Han Xiao, Minlie Huang, Xiaoyan Zhu

Knowledge graph embedding aims at offering a numerical knowledge representation paradigm by transforming the entities and relations into continuous vector space.

Knowledge Graph Embedding Link Prediction

TransG : A Generative Mixture Model for Knowledge Graph Embedding

no code implementations18 Sep 2015 Han Xiao, Minlie Huang, Yu Hao, Xiaoyan Zhu

Recently, knowledge graph embedding, which projects symbolic entities and relations into continuous vector space, has become a new, hot topic in artificial intelligence.

Knowledge Graph Embedding

TransA: An Adaptive Approach for Knowledge Graph Embedding

no code implementations18 Sep 2015 Han Xiao, Minlie Huang, Yu Hao, Xiaoyan Zhu

Knowledge representation is a major topic in AI, and many studies attempt to represent entities and relations of knowledge base in a continuous vector space.

Knowledge Graph Embedding Metric Learning

Knowlege Graph Embedding by Flexible Translation

no code implementations20 May 2015 Jun Feng, Mantong Zhou, Yu Hao, Minlie Huang, Xiaoyan Zhu

TransF regards relation as translation between head entity vector and tail entity vector with flexible magnitude.

General Classification Knowledge Graph Embedding +2

Robustly Leveraging Prior Knowledge in Text Classification

no code implementations3 Mar 2015 Biao Liu, Minlie Huang

Prior knowledge has been shown very useful to address many natural language processing tasks.

Classification General Classification +1

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