Search Results for author: Minlie Huang

Found 153 papers, 86 papers with code

Persona-Guided Planning for Controlling the Protagonist’s Persona in Story Generation

1 code implementation NAACL 2022 Zhexin Zhang, Jiaxin Wen, Jian Guan, Minlie Huang

In this paper, we aim to control the protagonist’s persona in story generation, i. e., generating a story from a leading context and a persona description, where the protagonist should exhibit the specified personality through a coherent event sequence.

Story Generation

Turn-Level User Satisfaction Estimation in E-commerce Customer Service

no code implementations ACL (ECNLP) 2021 Runze Liang, Ryuichi Takanobu, Feng-Lin Li, Ji Zhang, Haiqing Chen, Minlie Huang

To this end, we formalize the turn-level satisfaction estimation as a reinforcement learning problem, in which the model can be optimized with only session-level satisfaction labels.

When does Further Pre-training MLM Help? An Empirical Study on Task-Oriented Dialog Pre-training

1 code implementation EMNLP (insights) 2021 Qi Zhu, Yuxian Gu, Lingxiao Luo, Bing Li, Cheng Li, Wei Peng, Minlie Huang, Xiaoyan Zhu

Further pre-training language models on in-domain data (domain-adaptive pre-training, DAPT) or task-relevant data (task-adaptive pre-training, TAPT) before fine-tuning has been shown to improve downstream tasks’ performances.

Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models

no code implementations1 Feb 2023 Zhihong Shao, Yeyun Gong, Yelong Shen, Minlie Huang, Nan Duan, Weizhu Chen

However, the quality of the prompts depends on the demonstrations given to the models, and creating many of them by hand is costly.

PAL: Persona-Augmented Emotional Support Conversation Generation

no code implementations19 Dec 2022 Jiale Cheng, Sahand Sabour, Hao Sun, Zhuang Chen, Minlie Huang

As previous studies have demonstrated that seekers' persona is an important factor for effective support, we investigate whether there are benefits to modeling such information in dialogue models for support.

Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation

1 code implementation4 Dec 2022 Zhexin Zhang, Jiale Cheng, Hao Sun, Jiawen Deng, Fei Mi, Yasheng Wang, Lifeng Shang, Minlie Huang

In order to detect such toxic generations, existing methods rely on templates, real-world data extraction, crowdsourcing workers, or automatic generation to construct adversarial contexts that are likely to induce toxic generations.

Pretrained Language Models Response Generation

Chaining Simultaneous Thoughts for Numerical Reasoning

no code implementations29 Nov 2022 Zhihong Shao, Fei Huang, Minlie Huang

Given that rich information is hidden behind ubiquitous numbers in text, numerical reasoning over text should be an essential skill of AI systems.

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.

Aligning Recommendation and Conversation via Dual Imitation

no code implementations5 Nov 2022 Jinfeng Zhou, Bo wang, Minlie Huang, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou

Human conversations of recommendation naturally involve the shift of interests which can align the recommendation actions and conversation process to make accurate recommendations with rich explanations.

Recommendation Systems

Learning Instructions with Unlabeled Data for Zero-Shot Cross-Task Generalization

1 code implementation17 Oct 2022 Yuxian Gu, Pei Ke, Xiaoyan Zhu, Minlie Huang

Recently, instruction tuning (IT), which fine-tunes a pre-trained language model on a massive collection of tasks described via human-craft instructions, has been shown effective in instruction learning for unseen tasks.

Language Modelling

A Benchmark for Understanding and Generating Dialogue between Characters in Stories

no code implementations18 Sep 2022 Jianzhu Yao, Ziqi Liu, Jian Guan, Minlie Huang

We build a new dataset DialStory, which consists of 105k Chinese stories with a large amount of dialogue weaved into the plots to support the evaluation.

Dialogue Generation Speaker Recognition

StoryTrans: Non-Parallel Story Author-Style Transfer with Discourse Representations and Content Enhancing

no code implementations29 Aug 2022 Xuekai Zhu, Jian Guan, Minlie Huang, Juan Liu

Moreover, to enhance content preservation, we design a mask-and-fill framework to explicitly fuse style-specific keywords of source texts into generation.

Style Transfer Text Style Transfer

Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework

1 code implementation8 Aug 2022 Jian Guan, Zhenyu Yang, Rongsheng Zhang, Zhipeng Hu, Minlie Huang

Despite advances in generating fluent texts, existing pretraining models tend to attach incoherent event sequences to involved entities when generating narratives such as stories and news.

On the Learning of Non-Autoregressive Transformers

no code implementations13 Jun 2022 Fei Huang, Tianhua Tao, Hao Zhou, Lei LI, Minlie Huang

Non-autoregressive Transformer (NAT) is a family of text generation models, which aims to reduce the decoding latency by predicting the whole sentences in parallel.

Text Generation

Curriculum-Based Self-Training Makes Better Few-Shot Learners for Data-to-Text Generation

1 code implementation6 Jun 2022 Pei Ke, Haozhe Ji, Zhenyu Yang, Yi Huang, Junlan Feng, Xiaoyan Zhu, Minlie Huang

Despite the success of text-to-text pre-trained models in various natural language generation (NLG) tasks, the generation performance is largely restricted by the number of labeled data in downstream tasks, particularly in data-to-text generation tasks.

Data-to-Text Generation Unsupervised Pre-training

Many-Class Text Classification with Matching

no code implementations23 May 2022 Yi Song, Yuxian Gu, Minlie Huang

In this work, we formulate \textbf{T}ext \textbf{C}lassification as a \textbf{M}atching problem between the text and the labels, and propose a simple yet effective framework named TCM.

Classification Pretrained Language Models +2

Directed Acyclic Transformer for Non-Autoregressive Machine Translation

1 code implementation16 May 2022 Fei Huang, Hao Zhou, Yang Liu, Hang Li, Minlie Huang

Non-autoregressive Transformers (NATs) significantly reduce the decoding latency by generating all tokens in parallel.

Knowledge Distillation Machine Translation +1

Persona-Guided Planning for Controlling the Protagonist's Persona in Story Generation

1 code implementation22 Apr 2022 Zhexin Zhang, Jiaxin Wen, Jian Guan, Minlie Huang

Endowing the protagonist with a specific personality is essential for writing an engaging story.

Story Generation

LaMemo: Language Modeling with Look-Ahead Memory

1 code implementation NAACL 2022 Haozhe Ji, Rongsheng Zhang, Zhenyu Yang, Zhipeng Hu, Minlie Huang

Although Transformers with fully connected self-attentions are powerful to model long-term dependencies, they are struggling to scale to long texts with thousands of words in language modeling.

Language Modelling

Chat-Capsule: A Hierarchical Capsule for Dialog-level Emotion Analysis

no code implementations23 Mar 2022 Yequan Wang, Xuying Meng, Yiyi Liu, Aixin Sun, Yao Wang, Yinhe Zheng, Minlie Huang

These models hence are not optimized for dialog-level emotion detection, i. e. to predict the emotion category of a dialog as a whole.

Emotion Recognition

Continual Prompt Tuning for Dialog State Tracking

1 code implementation ACL 2022 Qi Zhu, Bing Li, Fei Mi, Xiaoyan Zhu, Minlie Huang

A desirable dialog system should be able to continually learn new skills without forgetting old ones, and thereby adapt to new domains or tasks in its life cycle.

Continual Learning dialog state tracking +1

Acceleration of Federated Learning with Alleviated Forgetting in Local Training

1 code implementation ICLR 2022 Chencheng Xu, Zhiwei Hong, Minlie Huang, Tao Jiang

Here, we propose FedReg, an algorithm to accelerate FL with alleviated knowledge forgetting in the local training stage by regularizing locally trained parameters with the loss on generated pseudo data, which encode the knowledge of previous training data learned by the global model.

Distributed Optimization Federated Learning

Rethinking and Refining the Distinct Metric

1 code implementation ACL 2022 Siyang Liu, Sahand Sabour, Yinhe Zheng, Pei Ke, Xiaoyan Zhu, Minlie Huang

We provide both empirical and theoretical evidence to show that our method effectively removes the biases existing in the original distinct score.

Text Generation

AugESC: Large-scale Data Augmentation for Emotional Support Conversation with Pre-trained Language Models

no code implementations26 Feb 2022 Chujie Zheng, Sahand Sabour, Jiaxin Wen, Minlie Huang

Lastly, we demonstrate with interactive evaluation that AugESC can further enhance dialog models tuned on ESConv to handle various conversation topics and to provide significantly more effective emotional support.

Data Augmentation Topic coverage

Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks

1 code implementation16 Feb 2022 Jingyan Zhou, Jiawen Deng, Fei Mi, Yitong Li, Yasheng Wang, Minlie Huang, Xin Jiang, Qun Liu, Helen Meng

The research of open-domain dialog systems has been greatly prospered by neural models trained on large-scale corpora, however, such corpora often introduce various safety problems (e. g., offensive languages, biases, and toxic behaviors) that significantly hinder the deployment of dialog systems in practice.

Bias Detection Open-Domain Dialog

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

COLD: A Benchmark for Chinese Offensive Language Detection

2 code implementations16 Jan 2022 Jiawen Deng, Jingyan Zhou, Hao Sun, Chujie Zheng, Fei Mi, Helen Meng, Minlie Huang

To this end, we propose a benchmark --COLD for Chinese offensive language analysis, including a Chinese Offensive Language Dataset --COLDATASET and a baseline detector --COLDETECTOR which is trained on the dataset.

Unsupervised Domain Adaptation with Adapter

no code implementations1 Nov 2021 Rongsheng Zhang, Yinhe Zheng, Xiaoxi Mao, Minlie Huang

However, fine-tuning all the parameters of the PrLM on a small domain-specific corpus distort the learned generic knowledge, and it is also expensive to deployment a whole fine-tuned PrLM for each domain.

Unsupervised Domain Adaptation

On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark

1 code implementation Findings (ACL) 2022 Hao Sun, Guangxuan Xu, Jiawen Deng, Jiale Cheng, Chujie Zheng, Hao Zhou, Nanyun Peng, Xiaoyan Zhu, Minlie Huang

We propose a taxonomy for dialogue safety specifically designed to capture unsafe behaviors in human-bot dialogue settings, with focuses on context-sensitive unsafety, which is under-explored in prior works.

Answering Open-Domain Multi-Answer Questions via a Recall-then-Verify Framework

1 code implementation ACL 2022 Zhihong Shao, Minlie Huang

Open-domain questions are likely to be open-ended and ambiguous, leading to multiple valid answers.

DiscoDVT: Generating Long Text with Discourse-Aware Discrete Variational Transformer

1 code implementation EMNLP 2021 Haozhe Ji, Minlie Huang

Despite the recent advances in applying pre-trained language models to generate high-quality texts, generating long passages that maintain long-range coherence is yet challenging for these models.

Story Generation

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

no code implementations14 Sep 2021 Chujie Zheng, Minlie Huang

In this work, we focus on the few-shot learning for grounded dialog generation (GDG).

Few-Shot Learning

CEM: Commonsense-aware Empathetic Response Generation

1 code implementation13 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 Response Generation

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

1 code implementation ACL 2022 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 Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation

2 code implementations30 Aug 2021 Jian Guan, Zhuoer Feng, Yamei Chen, Ruilin He, Xiaoxi Mao, Changjie Fan, Minlie Huang

Therefore, we propose a story-centric benchmark named LOT for evaluating Chinese long text modeling, which aggregates two understanding tasks and two generation tasks.

Text Infilling

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

1 code implementation EMNLP 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.

dialog state tracking Few-Shot Learning +4

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

2 code implementations3 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.

Story Generation

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

1 code implementation22 Jun 2021 Silin Gao, Ryuichi Takanobu, Antoine Bosselut, Minlie Huang

To address this task, we propose a TOD system with semi-structured knowledge management, SeKnow, which extends the belief state to manage knowledge with both structured and unstructured contents.

Language Modelling Management

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

2 code implementations20 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 implementation Findings (ACL) 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

1 code implementation 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 Yinhe Zheng, Yida Wang, Pei Ke, Zhenyu Yang, Minlie Huang

This paper propose to combine pretrained language models with the modular dialogue paradigm for open-domain dialogue modeling.

Informativeness Language Modelling +2

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

1 code implementation Findings (ACL) 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

2 code implementations Findings (ACL) 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

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.

Story 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

Stylized Story Generation with Style-Guided Planning

no code implementations Findings (ACL) 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.

Story Generation

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

1 code implementation Findings (ACL) 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 +1

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

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 implementation EMNLP 2021 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 Response Generation +1

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

3 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

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 Response 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.

Explanation Generation

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.

Story Generation

A Large-Scale Chinese Short-Text Conversation Dataset

2 code implementations10 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 +1

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

no code implementations SIGDIAL (ACL) 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

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

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.

reinforcement-learning reinforcement Learning

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 Story 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

2 code implementations12 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 +3

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

1 code implementation9 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 OOD Detection +1

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.

reinforcement-learning reinforcement Learning

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.

reinforcement-learning reinforcement Learning +1

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

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.

Response Generation

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

2 code implementations 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.

Retrieval

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 +3

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.

text similarity

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 reinforcement-learning +1

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 reinforcement-learning +2

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

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 Management +1

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.

Retrieval

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

6 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.

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 +1

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

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.

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 +2

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

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 +1

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

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 +3

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 +2

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