Search Results for author: Zhou Yu

Found 115 papers, 47 papers with code

DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs

1 code implementation SIGDIAL (ACL) 2021 Satwik Kottur, Chinnadhurai Sankar, Zhou Yu, Alborz Geramifard

Real-world conversational agents must effectively handle long conversations that span multiple contexts.

Effective Unsupervised Constrained Text Generation based on Perturbed Masking

no code implementations Findings (ACL) 2022 Yingwen Fu, Wenjie Ou, Zhou Yu, Yue Lin

Unsupervised constrained text generation aims to generate text under a given set of constraints without any supervised data.

Text Generation

KERS: A Knowledge-Enhanced Framework for Recommendation Dialog Systems with Multiple Subgoals

no code implementations Findings (EMNLP) 2021 Jun Zhang, Yan Yang, Chencai Chen, Liang He, Zhou Yu

Recommendation dialogs require the system to build a social bond with users to gain trust and develop affinity in order to increase the chance of a successful recommendation.

Question Answering Recommendation Systems +1

Improving Named Entity Recognition in Spoken Dialog Systems by Context and Speech Pattern Modeling

no code implementations SIGDIAL (ACL) 2021 Minh Nguyen, Zhou Yu

Deployed spoken dialog systems receive user input in the form of automatic speech recognition (ASR) transcripts, and simply applying NER model trained on written text to ASR transcripts often leads to low accuracy because compared to written text, ASR transcripts lack important cues such as punctuation and capitalization.

Automatic Speech Recognition named-entity-recognition +1

Learning a Better Initialization for Soft Prompts via Meta-Learning

no code implementations25 May 2022 Yukun Huang, Kun Qian, Zhou Yu

So pre-trained prompt tuning (PPT) is proposed to initialize prompts by leveraging pre-training data.

Meta-Learning

Just Fine-tune Twice: Selective Differential Privacy for Large Language Models

no code implementations15 Apr 2022 Weiyan Shi, Si Chen, Chiyuan Zhang, Ruoxi Jia, Zhou Yu

Because private information in language data is sparse, previous research formalized a Selective-Differential-Privacy (SDP) notion to provide protection for sensitive tokens detected by policy functions, and prove its effectiveness on RNN-based models.

FastKASSIM: A Fast Tree Kernel-Based Syntactic Similarity Metric

1 code implementation15 Mar 2022 Maximillian Chen, Caitlyn Chen, Xiao Yu, Zhou Yu

Syntax is a fundamental component of language, yet few metrics have been employed to capture syntactic similarity or coherence at the utterance- and document-level.

Random Forests Weighted Local Fréchet Regression with Theoretical Guarantee

no code implementations10 Feb 2022 Rui Qiu, Zhou Yu, Ruoqing Zhu

Based on the theory of infinite order U-processes and infinite order Mmn-estimator, we establish the consistency, rate of convergence, and asymptotic normality for our proposed random forests weighted Fr\'echet regression estimator, which covers the current large sample theory of random forests with Euclidean responses as a special case.

Optimal Model Averaging of Support Vector Machines in Diverging Model Spaces

no code implementations24 Dec 2021 Chaoxia Yuan, Chao Ying, Zhou Yu, Fang Fang

Support vector machine (SVM) is a powerful classification method that has achieved great success in many fields.

Model Selection

Insta-VAX: A Multimodal Benchmark for Anti-Vaccine and Misinformation Posts Detection on Social Media

no code implementations15 Dec 2021 Mingyang Zhou, Mahasweta Chakraborti, Sijia Qian, Zhou Yu, Jingwen Zhang

The dataset and classifiers contribute to monitoring and tracking of vaccine discussions for social scientific and public health efforts in combating the problem of vaccine misinformation.

Misinformation

Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation

no code implementations15 Dec 2021 Yu Li, Baolin Peng, Yelong Shen, Yi Mao, Lars Liden, Zhou Yu, Jianfeng Gao

To address these challenges, we present PLUG, a language model that homogenizes different knowledge sources to a unified knowledge representation for knowledge-grounded dialogue generation tasks.

Dialogue Generation Language Modelling

AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All

no code implementations15 Dec 2021 Lei Zuo, Kun Qian, Bowen Yang, Zhou Yu

A commonly observed problem of the state-of-the-art natural language technologies, such as Amazon Alexa and Apple Siri, is that their services do not extend to most developing countries' citizens due to language barriers.

Meta-Learning

Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta Information

1 code implementation15 Dec 2021 Bowen Yang, Cong Han, Yu Li, Lei Zuo, Zhou Yu

The encoder learns to map item metadata to embeddings that can reflect the semantic information in the dialog context.

Language Modelling Recommendation Systems +1

Database Search Results Disambiguation for Task-Oriented Dialog Systems

no code implementations15 Dec 2021 Kun Qian, Ahmad Beirami, Satwik Kottur, Shahin Shayandeh, Paul Crook, Alborz Geramifard, Zhou Yu, Chinnadhurai Sankar

We find that training on our augmented dialog data improves the model's ability to deal with ambiguous scenarios, without sacrificing performance on unmodified turns.

Multi-Task Learning

DG2: Data Augmentation Through Document Grounded Dialogue Generation

no code implementations15 Dec 2021 Qingyang Wu, Song Feng, Derek Chen, Sachindra Joshi, Luis A. Lastras, Zhou Yu

Collecting data for training dialog systems can be extremely expensive due to the involvement of human participants and need for extensive annotation.

Data Augmentation Dialogue Generation

ErAConD : Error Annotated Conversational Dialog Dataset for Grammatical Error Correction

1 code implementation15 Dec 2021 Xun Yuan, Derek Pham, Sam Davidson, Zhou Yu

Currently available grammatical error correction (GEC) datasets are compiled using well-formed written text, limiting the applicability of these datasets to other domains such as informal writing and dialog.

Chatbot Grammatical Error Correction

IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning

1 code implementation25 Oct 2021 Pan Lu, Liang Qiu, Jiaqi Chen, Tony Xia, Yizhou Zhao, Wei zhang, Zhou Yu, Xiaodan Liang, Song-Chun Zhu

Also, we develop a strong IconQA baseline Patch-TRM that applies a pyramid cross-modal Transformer with input diagram embeddings pre-trained on the icon dataset.

Arithmetic Reasoning Object Recognition +3

Clean or Annotate: How to Spend a Limited Data Collection Budget

no code implementations15 Oct 2021 Derek Chen, Zhou Yu, Samuel R. Bowman

Crowdsourcing platforms are often used to collect datasets for training machine learning models, despite higher levels of inaccurate labeling compared to expert labeling.

Denoising Learning with noisy labels +1

Zero-Shot Dialogue State Tracking via Cross-Task Transfer

1 code implementation EMNLP 2021 Zhaojiang Lin, Bing Liu, Andrea Madotto, Seungwhan Moon, Paul Crook, Zhenpeng Zhou, Zhiguang Wang, Zhou Yu, Eunjoon Cho, Rajen Subba, Pascale Fung

Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data.

Dialogue State Tracking Question Answering +1

GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation

1 code implementation EMNLP 2021 Derek Chen, Zhou Yu

Practical dialogue systems require robust methods of detecting out-of-scope (OOS) utterances to avoid conversational breakdowns and related failure modes.

Data Augmentation

Selective Differential Privacy for Language Modeling

1 code implementation30 Aug 2021 Weiyan Shi, Aiqi Cui, Evan Li, Ruoxi Jia, Zhou Yu

Given that the private information in natural language is sparse (for example, the bulk of an email might not carry personally identifiable information), we propose a new privacy notion, selective differential privacy, to provide rigorous privacy guarantees on the sensitive portion of the data to improve model utility.

Language Modelling Privacy Preserving

ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration

1 code implementation16 Aug 2021 Yuhao Cui, Zhou Yu, Chunqi Wang, Zhongzhou Zhao, Ji Zhang, Meng Wang, Jun Yu

Nevertheless, most existing VLP approaches have not fully utilized the intrinsic knowledge within the image-text pairs, which limits the effectiveness of the learned alignments and further restricts the performance of their models.

Discovering Dialogue Slots with Weak Supervision

no code implementations ACL 2021 Vojt{\v{e}}ch Hude{\v{c}}ek, Ond{\v{r}}ej Du{\v{s}}ek, Zhou Yu

Our model demonstrates state-of-the-art performance in slot tagging without labeled training data on four different dialogue domains.

Response Generation Task-Oriented Dialogue Systems

The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity

no code implementations ACL 2021 David Gros, Yu Li, Zhou Yu

Humans are increasingly interacting with machines through language, sometimes in contexts where the user may not know they are talking to a machine (like over the phone or a text chatbot).

Chatbot

Discovering Chatbot's Self-Disclosure's Impact on User Trust, Affinity, and Recommendation Effectiveness

no code implementations3 Jun 2021 Kai-Hui Liang, Weiyan Shi, Yoojung Oh, Jingwen Zhang, Zhou Yu

In recent years, chatbots have been empowered to engage in social conversations with humans and have the potential to elicit people to disclose their personal experiences, opinions, and emotions.

Chatbot

SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues

no code implementations ACL 2021 Liang Qiu, Yuan Liang, Yizhou Zhao, Pan Lu, Baolin Peng, Zhou Yu, Ying Nian Wu, Song-Chun Zhu

Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly.

Dialog Relation Extraction

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.

Annotation Inconsistency and Entity Bias in MultiWOZ

no code implementations SIGDIAL (ACL) 2021 Kun Qian, Ahmad Beirami, Zhouhan Lin, Ankita De, Alborz Geramifard, Zhou Yu, Chinnadhurai Sankar

In this work, we identify an overlooked issue with dialog state annotation inconsistencies in the dataset, where a slot type is tagged inconsistently across similar dialogs leading to confusion for DST modeling.

Text Generation

Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking

1 code implementation10 May 2021 Zhaojiang Lin, Bing Liu, Seungwhan Moon, Paul Crook, Zhenpeng Zhou, Zhiguang Wang, Zhou Yu, Andrea Madotto, Eunjoon Cho, Rajen Subba

Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data.

Dialogue State Tracking Transfer Learning

LEGOEval: An Open-Source Toolkit for Dialogue System Evaluation via Crowdsourcing

1 code implementation ACL 2021 Yu Li, Josh Arnold, Feifan Yan, Weiyan Shi, Zhou Yu

We present LEGOEval, an open-source toolkit that enables researchers to easily evaluate dialogue systems in a few lines of code using the online crowdsource platform, Amazon Mechanical Turk.

Revealing Persona Biases in Dialogue Systems

1 code implementation18 Apr 2021 Emily Sheng, Josh Arnold, Zhou Yu, Kai-Wei Chang, Nanyun Peng

Dialogue systems in the form of chatbots and personal assistants are being increasingly integrated into people's lives.

DEUX: An Attribute-Guided Framework for Sociable Recommendation Dialog Systems

no code implementations16 Apr 2021 Yu Li, Shirley Anugrah Hayati, Weiyan Shi, Zhou Yu

It is important for sociable recommendation dialog systems to perform as both on-task content and social content to engage users and gain their favor.

A Student-Teacher Architecture for Dialog Domain Adaptation under the Meta-Learning Setting

no code implementations6 Apr 2021 Kun Qian, Wei Wei, Zhou Yu

The most recent researches on domain adaption focus on giving the model a better initialization, rather than optimizing the adaptation process.

Domain Adaptation Meta-Learning

MIDAS: A Dialog Act Annotation Scheme for Open Domain HumanMachine Spoken Conversations

no code implementations EACL 2021 Dian Yu, Zhou Yu

To validate our scheme, we leveraged transfer learning methods to train a multi-label dialog act prediction model and reached an F1 score of 0. 79.

Transfer Learning

Attribute Alignment: Controlling Text Generation from Pre-trained Language Models

1 code implementation Findings (EMNLP) 2021 Dian Yu, Zhou Yu, Kenji Sagae

Large language models benefit from training with a large amount of unlabeled text, which gives them increasingly fluent and diverse generation capabilities.

Language Modelling Text Generation

Towards Socially Intelligent Agents with Mental State Transition and Human Utility

no code implementations12 Mar 2021 Liang Qiu, Yizhou Zhao, Yuan Liang, Pan Lu, Weiyan Shi, Zhou Yu, Song-Chun Zhu

Building a socially intelligent agent involves many challenges, one of which is to track the agent's mental state transition and teach the agent to make rational decisions guided by its utility like a human.

ChainCQG: Flow-Aware Conversational Question Generation

1 code implementation EACL 2021 Jing Gu, Mostafa Mirshekari, Zhou Yu, Aaron Sisto

Conversational systems enable numerous valuable applications, and question-answering is an important component underlying many of these.

Conversational Question Answering Question Generation

Refine and Imitate: Reducing Repetition and Inconsistency in Dialogue Generation via Reinforcement Learning and Human Demonstration

no code implementations1 Jan 2021 Weiyan Shi, Yu Li, Saurav Sahay, Zhou Yu

Despite the recent success of large-scale language models on various downstream NLP tasks, the repetition and inconsistency problems still persist in dialogue response generation.

Dialogue Generation Language Modelling +1

Sufficient and Disentangled Representation Learning

no code implementations1 Jan 2021 Jian Huang, Yuling Jiao, Xu Liao, Jin Liu, Zhou Yu

We provide strong statistical guarantees for the learned representation by establishing an upper bound on the excess error of the objective function and show that it reaches the nonparametric minimax rate under mild conditions.

Disentanglement

Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration

no code implementations Findings (EMNLP) 2021 Weiyan Shi, Yu Li, Saurav Sahay, Zhou Yu

Despite the recent success of large-scale language models on various downstream NLP tasks, the repetition and inconsistency problems still persist in dialogue response generation.

Language Modelling Response Generation

Continual Learning in Task-Oriented Dialogue Systems

1 code implementation EMNLP 2021 Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou, Seungwhan Moon, Paul Crook, Bing Liu, Zhou Yu, Eunjoon Cho, Zhiguang Wang

Continual learning in task-oriented dialogue systems can allow us to add new domains and functionalities through time without incurring the high cost of a whole system retraining.

Continual Learning Multi-Task Learning +2

Code to Comment "Translation": Data, Metrics, Baselining & Evaluation

no code implementations3 Oct 2020 David Gros, Hariharan Sezhiyan, Prem Devanbu, Zhou Yu

We carefully examine the underlying assumption here: that the task of generating comments sufficiently resembles the task of translating between natural languages, and so similar models and evaluation metrics could be used.

Information Retrieval Translation

INSPIRED: Toward Sociable Recommendation Dialog Systems

1 code implementation EMNLP 2020 Shirley Anugrah Hayati, Dongyeop Kang, Qingxiaoyang Zhu, Weiyan Shi, Zhou Yu

To better understand how humans make recommendations in communication, we design an annotation scheme related to recommendation strategies based on social science theories and annotate these dialogs.

ALICE: Active Learning with Contrastive Natural Language Explanations

no code implementations EMNLP 2020 Weixin Liang, James Zou, Zhou Yu

We propose Active Learning with Contrastive Explanations (ALICE), an expert-in-the-loop training framework that utilizes contrastive natural language explanations to improve data efficiency in learning.

Active Learning Classification +1

Structured Attention for Unsupervised Dialogue Structure Induction

1 code implementation EMNLP 2020 Liang Qiu, Yizhou Zhao, Weiyan Shi, Yuan Liang, Feng Shi, Tao Yuan, Zhou Yu, Song-Chun Zhu

Inducing a meaningful structural representation from one or a set of dialogues is a crucial but challenging task in computational linguistics.

Inductive Bias Sentence Embeddings

Perception Score, A Learned Metric for Open-ended Text Generation Evaluation

no code implementations7 Aug 2020 Jing Gu, Qingyang Wu, Zhou Yu

Automatic evaluation for open-ended natural language generation tasks remains a challenge.

Text Generation

Deep Dimension Reduction for Supervised Representation Learning

1 code implementation10 Jun 2020 Jian Huang, Yuling Jiao, Xu Liao, Jin Liu, Zhou Yu

We propose a deep dimension reduction approach to learning representations with these characteristics.

Dimensionality Reduction Disentanglement

Deep Multimodal Neural Architecture Search

no code implementations25 Apr 2020 Zhou Yu, Yuhao Cui, Jun Yu, Meng Wang, DaCheng Tao, Qi Tian

Most existing works focus on a single task and design neural architectures manually, which are highly task-specific and hard to generalize to different tasks.

Neural Architecture Search Question Answering +3

A Tailored Pre-Training Model for Task-Oriented Dialog Generation

1 code implementation24 Apr 2020 Jing Gu, Qingyang Wu, Chongruo wu, Weiyan Shi, Zhou Yu

The recent success of large pre-trained language models such as BERT and GPT-2 has suggested the effectiveness of incorporating language priors in downstream dialog generation tasks.

Knowledge Distillation Language Modelling

Paraphrase Augmented Task-Oriented Dialog Generation

1 code implementation ACL 2020 Silin Gao, Yichi Zhang, Zhijian Ou, Zhou Yu

Neural generative models have achieved promising performance on dialog generation tasks if given a huge data set.

Data Augmentation Response Generation

TextGAIL: Generative Adversarial Imitation Learning for Text Generation

no code implementations7 Apr 2020 Qingyang Wu, Lei LI, Zhou Yu

Generative Adversarial Networks (GANs) for text generation have recently received many criticisms, as they perform worse than their MLE counterparts.

Conditional Text Generation Imitation Learning

Weakly-Supervised Multi-Level Attentional Reconstruction Network for Grounding Textual Queries in Videos

no code implementations16 Mar 2020 Yijun Song, Jingwen Wang, Lin Ma, Zhou Yu, Jun Yu

The task of temporally grounding textual queries in videos is to localize one video segment that semantically corresponds to the given query.

Matching Text with Deep Mutual Information Estimation

no code implementations9 Mar 2020 Xixi Zhou, Chengxi Li, Jiajun Bu, Chengwei Yao, Keyue Shi, Zhi Yu, Zhou Yu

Our approach, Text matching with Deep Info Max (TIM), is integrated with a procedure of unsupervised learning of representations by maximizing the mutual information between text matching neural network's input and output.

Answer Selection Mutual Information Estimation +4

Distributed estimation of principal support vector machines for sufficient dimension reduction

no code implementations28 Nov 2019 Jun Jin, Chao Ying, Zhou Yu

The principal support vector machines method (Li et al., 2011) is a powerful tool for sufficient dimension reduction that replaces original predictors with their low-dimensional linear combinations without loss of information.

Dimensionality Reduction

End-to-End Trainable Non-Collaborative Dialog System

1 code implementation25 Nov 2019 Yu Li, Kun Qian, Weiyan Shi, Zhou Yu

End-to-end task-oriented dialog models have achieved promising performance on collaborative tasks where users willingly coordinate with the system to complete a given task.

Filling Conversation Ellipsis for Better Social Dialog Understanding

no code implementations25 Nov 2019 Xiyuan Zhang, Chengxi Li, Dian Yu, Samuel Davidson, Zhou Yu

We then train a prediction model using both utterances containing ellipsis and our automatically completed utterances.

Semantic Role Labeling Sentence Completion

Importance-Aware Learning for Neural Headline Editing

no code implementations25 Nov 2019 Qingyang Wu, Lei LI, Hao Zhou, Ying Zeng, Zhou Yu

We propose to automate this headline editing process through neural network models to provide more immediate writing support for these social media news writers.

Headline generation

Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context

5 code implementations24 Nov 2019 Yichi Zhang, Zhijian Ou, Zhou Yu

Conversations have an intrinsic one-to-many property, which means that multiple responses can be appropriate for the same dialog context.

Data Augmentation End-To-End Dialogue Modelling

Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models

1 code implementation EACL 2021 Qingyang Wu, Yichi Zhang, Yu Li, Zhou Yu

Existing dialog system models require extensive human annotations and are difficult to generalize to different tasks.

Language Modelling Response Generation

MOSS: End-to-End Dialog System Framework with Modular Supervision

1 code implementation12 Sep 2019 Weixin Liang, Youzhi Tian, Chengcai Chen, Zhou Yu

To utilize limited training data more efficiently, we propose Modular Supervision Network (MOSS), an encoder-decoder training framework that could incorporate supervision from various intermediate dialog system modules including natural language understanding, dialog state tracking, dialog policy learning, and natural language generation.

Natural Language Understanding Text Generation

Dependency Parsing for Spoken Dialog Systems

no code implementations IJCNLP 2019 Sam Davidson, Dian Yu, Zhou Yu

Dependency parsing of conversational input can play an important role in language understanding for dialog systems by identifying the relationships between entities extracted from user utterances.

Dependency Parsing

How to Build User Simulators to Train RL-based Dialog Systems

1 code implementation IJCNLP 2019 Weiyan Shi, Kun Qian, Xuewei Wang, Zhou Yu

We propose a method of standardizing user simulator building that can be used by the community to compare dialog system quality using the same set of user simulators fairly.

A Large-Scale User Study of an Alexa Prize Chatbot: Effect of TTS Dynamism on Perceived Quality of Social Dialog

no code implementations WS 2019 Michelle Cohn, Chun-Yen Chen, Zhou Yu

This study tests the effect of cognitive-emotional expression in an Alexa text-to-speech (TTS) voice on users{'} experience with a social dialog system.

Chatbot

MIDAS: A Dialog Act Annotation Scheme for Open Domain Human Machine Spoken Conversations

1 code implementation27 Aug 2019 Dian Yu, Zhou Yu

Previous dialog act schemes, such as SWBD-DAMSL, are designed for human-human conversations, in which conversation partners have perfect language understanding ability.

Transfer Learning

Multimodal Unified Attention Networks for Vision-and-Language Interactions

no code implementations12 Aug 2019 Zhou Yu, Yuhao Cui, Jun Yu, DaCheng Tao, Qi Tian

Learning an effective attention mechanism for multimodal data is important in many vision-and-language tasks that require a synergic understanding of both the visual and textual contents.

Question Answering Visual Grounding +2

Deep Modular Co-Attention Networks for Visual Question Answering

7 code implementations CVPR 2019 Zhou Yu, Jun Yu, Yuhao Cui, DaCheng Tao, Qi Tian

In this paper, we propose a deep Modular Co-Attention Network (MCAN) that consists of Modular Co-Attention (MCA) layers cascaded in depth.

Question Answering Visual Question Answering +1

Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good

2 code implementations ACL 2019 Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, Zhou Yu

Developing intelligent persuasive conversational agents to change people's opinions and actions for social good is the frontier in advancing the ethical development of automated dialogue systems.

Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks

no code implementations11 Jun 2019 Qingyang Wu, He Li, Lexin Li, Zhou Yu

With the widespread success of deep neural networks in science and technology, it is becoming increasingly important to quantify the uncertainty of the predictions produced by deep learning.

Classification General Classification +1

Domain Adaptive Dialog Generation via Meta Learning

1 code implementation ACL 2019 Kun Qian, Zhou Yu

We train a dialog system model using multiple rich-resource single-domain dialog data by applying the model-agnostic meta-learning algorithm to dialog domain.

Domain Adaptation Meta-Learning

Multimodal Transformer with Multi-View Visual Representation for Image Captioning

no code implementations20 May 2019 Jun Yu, Jing Li, Zhou Yu, Qingming Huang

Despite the success of existing studies, current methods only model the co-attention that characterizes the inter-modal interactions while neglecting the self-attention that characterizes the intra-modal interactions.

Image Captioning Machine Translation

Single Pixel Reconstruction for One-stage Instance Segmentation

no code implementations16 Apr 2019 Jun Yu, Jinghan Yao, Jian Zhang, Zhou Yu, DaCheng Tao

In this paper, we propose a one-stage framework, SPRNet, which performs efficient instance segmentation by introducing a single pixel reconstruction (SPR) branch to off-the-shelf one-stage detectors.

Instance Segmentation Region Proposal +1

Unsupervised Dialog Structure Learning

1 code implementation NAACL 2019 Weiyan Shi, Tiancheng Zhao, Zhou Yu

The learned dialog structure can shed light on how to analyze human dialogs, and more importantly contribute to the design and evaluation of dialog systems.

Incorporating Structured Commonsense Knowledge in Story Completion

no code implementations1 Nov 2018 Jiaao Chen, Jianshu Chen, Zhou Yu

The ability to select an appropriate story ending is the first step towards perfect narrative comprehension.

Story Completion

Structured Content Preservation for Unsupervised Text Style Transfer

2 code implementations15 Oct 2018 Youzhi Tian, Zhiting Hu, Zhou Yu

Text style transfer aims to modify the style of a sentence while keeping its content unchanged.

Language Modelling Style Transfer +2

Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content

2 code implementations EMNLP 2018 Weiming Wen, Songwen Su, Zhou Yu

With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks.

Semantic Similarity Semantic Textual Similarity

Overlapping Sliced Inverse Regression for Dimension Reduction

no code implementations23 Jun 2018 Ning Zhang, Zhou Yu, Qiang Wu

The new algorithm, called overlapping sliced inverse regression (OSIR), is able to estimate the effective dimension reduction space and determine the number of effective factors more accurately.

Dimensionality Reduction

Multimodal Hierarchical Reinforcement Learning Policy for Task-Oriented Visual Dialog

no code implementations WS 2018 Jiaping Zhang, Tiancheng Zhao, Zhou Yu

We propose a multimodal hierarchical reinforcement learning framework that dynamically integrates vision and language for task-oriented visual dialog.

Hierarchical Reinforcement Learning reinforcement-learning +2

Sentiment Adaptive End-to-End Dialog Systems

no code implementations ACL 2018 Weiyan Shi, Zhou Yu

End-to-end learning framework is useful for building dialog systems for its simplicity in training and efficiency in model updating.

reinforcement-learning

Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering

2 code implementations10 Aug 2017 Zhou Yu, Jun Yu, Chenchao Xiang, Jianping Fan, DaCheng Tao

For fine-grained image and question representations, a `co-attention' mechanism is developed by using a deep neural network architecture to jointly learn the attentions for both the image and the question, which can allow us to reduce the irrelevant features effectively and obtain more discriminative features for image and question representations.

Question Answering Visual Question Answering +1

Multi-modal Factorized Bilinear Pooling with Co-Attention Learning for Visual Question Answering

6 code implementations ICCV 2017 Zhou Yu, Jun Yu, Jianping Fan, DaCheng Tao

For multi-modal feature fusion, here we develop a Multi-modal Factorized Bilinear (MFB) pooling approach to efficiently and effectively combine multi-modal features, which results in superior performance for VQA compared with other bilinear pooling approaches.

Question Answering Visual Question Answering +1

Learning Conversational Systems that Interleave Task and Non-Task Content

no code implementations1 Mar 2017 Zhou Yu, Alan W. black, Alexander I. Rudnicky

These systems work well when users have clear and explicit intentions that are well-aligned to the systems' capabilities.

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