103 citations · 142 across the 24 of their papers we have counts for
24 papers
AKEM: Aligning Knowledge Base to Queries with Ensemble Model for Entity Recognition and Linking
Di Lu, Zhongping Liang, Caixia Yuan +1
This paper presents a novel approach to address the Entity Recognition and Linking Challenge at NLPCC 2015. The task involves extracting named entity mentions from short search que…
Whether you can locate or not? Interactive Referring Expression Generation
Fulong Ye, Yuxing Long, Fangxiang Feng +1
Referring Expression Generation (REG) aims to generate unambiguous Referring Expressions (REs) for objects in a visual scene, with a dual task of Referring Expression Comprehension…
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion Recognition
Yuzhao Mao, Di Lu, Xiaojie Wang +1
This paper concentrates on the understanding of interlocutors' emotions evoked in conversational utterances. Previous studies in this literature mainly focus on more accurate emoti…
Enhancing Feature Extraction for Indoor Fingerprint Localization Using Diversified Data
Jiyu Jiao, Xiaojun Wang, Chenlin He
Given the rapid advancements in wireless communication and terminal devices, high-speed and convenient WiFi has permeated various aspects of people's lives, and attention has been…
Multimodal Recommendation Dialog with Subjective Preference: A New Challenge and Benchmark
Yuxing Long, Binyuan Hui, Caixia Yuan1 +3
Existing multimodal task-oriented dialog data fails to demonstrate the diverse expressions of user subjective preferences and recommendation acts in the real-life shopping scenario…
An Asynchronous Updating Reinforcement Learning Framework for Task-oriented Dialog System
Sai Zhang, Yuwei Hu, Xiaojie Wang +1
Reinforcement learning has been applied to train the dialog systems in many works. Previous approaches divide the dialog system into multiple modules including DST (dialog state tr…
SPRING: Situated Conversation Agent Pretrained with Multimodal Questions from Incremental Layout Graph
Yuxing Long, Binyuan Hui, Fulong Ye +5
Existing multimodal conversation agents have shown impressive abilities to locate absolute positions or retrieve attributes in simple scenarios, but they fail to perform well when…
Towards Unifying Reference Expression Generation and Comprehension
Duo Zheng, Tao Kong, Ya Jing +2
Reference Expression Generation (REG) and Comprehension (REC) are two highly correlated tasks. Modeling REG and REC simultaneously for utilizing the relation between them is a prom…
GR-GAN: Gradual Refinement Text-to-image Generation
Bo Yang, Fangxiang Feng, Xiaojie Wang
A good Text-to-Image model should not only generate high quality images, but also ensure the consistency between the text and the generated image. Previous models failed to simulta…
Question-Driven Graph Fusion Network For Visual Question Answering
Yuxi Qian, Yuncong Hu, Ruonan Wang +2
Existing Visual Question Answering (VQA) models have explored various visual relationships between objects in the image to answer complex questions, which inevitably introduces irr…
Co-VQA : Answering by Interactive Sub Question Sequence
Ruonan Wang, Yuxi Qian, Fangxiang Feng +2
Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions…
A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots
Sai Zhang, Yuwei Hu, Yuchuan Wu +5
A slot value might be provided segment by segment over multiple-turn interactions in a dialog, especially for some important information such as phone numbers and names. It is a co…
Spot the Difference: A Cooperative Object-Referring Game in Non-Perfectly Co-Observable Scene
Duo Zheng, Fandong Meng, Qingyi Si +5
Visual dialog has witnessed great progress after introducing various vision-oriented goals into the conversation, especially such as GuessWhich and GuessWhat, where the only image…
Deep Keyphrase Completion
Yu Zhao, Jia Song, Huali Feng +4
Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text r…
Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue
Han Liu, Caixia Yuan, Xiaojie Wang +3
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue. To benchmark pr…
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Yuzhao Mao, Qi Sun, Guang Liu +4
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems. Existing studies on ERC primarily focus on summarizing the context informatio…
Answer-Driven Visual State Estimator for Goal-Oriented Visual Dialogue
Zipeng Xu, Fangxiang Feng, Xiaojie Wang +3
A goal-oriented visual dialogue involves multi-turn interactions between two agents, Questioner and Oracle. During which, the answer given by Oracle is of great significance, as it…
Label-Wise Document Pre-Training for Multi-Label Text Classification
Han Liu, Caixia Yuan, Xiaojie Wang
A major challenge of multi-label text classification (MLTC) is to stimulatingly exploit possible label differences and label correlations. In this paper, we tackle this challenge b…
Connecting Embeddings for Knowledge Graph Entity Typing
Yu Zhao, Anxiang Zhang, Ruobing Xie +2
Knowledge graph (KG) entity typing aims at inferring possible missing entity type instances in KG, which is a very significant but still under-explored subtask of knowledge graph c…
Guessing State Tracking for Visual Dialogue
Wei Pang, Xiaojie Wang
The Guesser is a task of visual grounding in GuessWhat?! like visual dialogue. It locates the target object in an image supposed by an Oracle oneself over a question-answer based d…
Visual Dialogue State Tracking for Question Generation
Wei Pang, Xiaojie Wang
GuessWhat?! is a visual dialogue task between a guesser and an oracle. The guesser aims to locate an object supposed by the oracle oneself in an image by asking a sequence of Yes/N…
Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue
Yue Ma, Xiaojie Wang, Zhenjiang Dong +1
This paper proposes a deep neural network model for joint modeling Natural Language Understanding (NLU) and Dialogue Management (DM) in goal-driven dialogue systems. There are thre…
Deep Reason: A Strong Baseline for Real-World Visual Reasoning
Chenfei Wu, Yanzhao Zhou, Gen Li +3
This paper presents a strong baseline for real-world visual reasoning (GQA), which achieves 60.93% in GQA 2019 challenge and won the sixth place. GQA is a large dataset with 22M qu…
Challenges in Representation Learning: A report on three machine learning contests
Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier +25
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the…