Search Results for author: Lizi Liao

Found 31 papers, 12 papers with code

Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers

no code implementations7 Apr 2024 Libo Qin, Qiguang Chen, YuHang Zhou, Zhi Chen, Yinghui Li, Lizi Liao, Min Li, Wanxiang Che, Philip S. Yu

To this end, in this paper, we present a thorough review and provide a unified perspective to summarize the recent progress as well as emerging trends in multilingual large language models (MLLMs) literature.

Language Modelling Large Language Model

SGSH: Stimulate Large Language Models with Skeleton Heuristics for Knowledge Base Question Generation

1 code implementation2 Apr 2024 Shasha Guo, Lizi Liao, Jing Zhang, Yanling Wang, Cuiping Li, Hong Chen

Knowledge base question generation (KBQG) aims to generate natural language questions from a set of triplet facts extracted from KB.

Question Generation Question-Generation

Mix-Initiative Response Generation with Dynamic Prefix Tuning

no code implementations26 Mar 2024 Yuxiang Nie, Heyan Huang, Xian-Ling Mao, Lizi Liao

Specifically, IDPT decouples initiative factors into different prefix parameters and uses the attention mechanism to adjust the selection of initiatives in guiding generation dynamically.

Response Generation

Multi-party Response Generation with Relation Disentanglement

no code implementations16 Mar 2024 Tianhao Dai, Chengyu Huang, Lizi Liao

Existing neural response generation models have achieved impressive improvements for two-party conversations, which assume that utterances are sequentially organized.

Disentanglement Relation +1

Learning to Ask Critical Questions for Assisting Product Search

no code implementations5 Mar 2024 Zixuan Li, Lizi Liao, Tat-Seng Chua

In this paper, we propose a dual-learning model that hybrids the best from both implicit session feedback and proactively clarifying with users on the most critical questions.

Information Retrieval

Contrastive Pre-training for Deep Session Data Understanding

no code implementations5 Mar 2024 Zixuan Li, Lizi Liao, Yunshan Ma, Tat-Seng Chua

In this work, we delve into deep session data understanding via scrutinizing the various clues inside the rich information in user sessions.

Contrastive Learning

A Survey on Neural Question Generation: Methods, Applications, and Prospects

no code implementations28 Feb 2024 Shasha Guo, Lizi Liao, Cuiping Li, Tat-Seng Chua

In this survey, we present a detailed examination of the advancements in Neural Question Generation (NQG), a field leveraging neural network techniques to generate relevant questions from diverse inputs like knowledge bases, texts, and images.

Question Generation Question-Generation

Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought

1 code implementation23 Dec 2023 Li Zheng, Hao Fei, Fei Li, Bobo Li, Lizi Liao, Donghong Ji, Chong Teng

With the proliferation of dialogic data across the Internet, the Dialogue Commonsense Multi-choice Question Answering (DC-MCQ) task has emerged as a response to the challenge of comprehending user queries and intentions.

Question Answering

End-to-end Task-oriented Dialogue: A Survey of Tasks, Methods, and Future Directions

no code implementations15 Nov 2023 Libo Qin, Wenbo Pan, Qiguang Chen, Lizi Liao, Zhou Yu, Yue Zhang, Wanxiang Che, Min Li

End-to-end task-oriented dialogue (EToD) can directly generate responses in an end-to-end fashion without modular training, which attracts escalating popularity.

Building Emotional Support Chatbots in the Era of LLMs

no code implementations17 Aug 2023 Zhonghua Zheng, Lizi Liao, Yang Deng, Liqiang Nie

The integration of emotional support into various conversational scenarios presents profound societal benefits, such as social interactions, mental health counseling, and customer service.

In-Context Learning Navigate

Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition

no code implementations8 Aug 2023 Bobo Li, Hao Fei, Lizi Liao, Yu Zhao, Chong Teng, Tat-Seng Chua, Donghong Ji, Fei Li

On the other hand, during the feature fusion stage, we propose a Contribution-aware Fusion Mechanism (CFM) and a Context Refusion Mechanism (CRM) for multimodal and context integration, respectively.

Contrastive Learning Disentanglement +2

REAL: A Representative Error-Driven Approach for Active Learning

1 code implementation3 Jul 2023 Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du

Given a limited labeling budget, active learning (AL) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training.

Active Learning Informativeness +2

Revisiting Conversation Discourse for Dialogue Disentanglement

no code implementations6 Jun 2023 Bobo Li, Hao Fei, Fei Li, Shengqiong Wu, Lizi Liao, Yinwei Wei, Tat-Seng Chua, Donghong Ji

Conversation utterances are essentially organized and described by the underlying discourse, and thus dialogue disentanglement requires the full understanding and harnessing of the intrinsic discourse attribute.

Attribute Disentanglement

Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration

1 code implementation23 May 2023 Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua

Conversational systems based on Large Language Models (LLMs), such as ChatGPT, show exceptional proficiency in context understanding and response generation.

Descriptive Response Generation

Actively Discovering New Slots for Task-oriented Conversation

1 code implementation6 May 2023 Yuxia Wu, Tianhao Dai, Zhedong Zheng, Lizi Liao

Existing task-oriented conversational search systems heavily rely on domain ontologies with pre-defined slots and candidate value sets.

Active Learning Conversational Search

Conversation Disentanglement with Bi-Level Contrastive Learning

no code implementations27 Oct 2022 Chengyu Huang, Zheng Zhang, Hao Fei, Lizi Liao

Conversation disentanglement aims to group utterances into detached sessions, which is a fundamental task in processing multi-party conversations.

Contrastive Learning Conversation Disentanglement +1

Structured and Natural Responses Co-generation for Conversational Search

1 code implementation ACM SIGIR Conference on Research and Development in Information Retrieval 2022 Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua

Existing approaches either 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses directly in an end-to-end manner.

Conversational Search

Decoupling Strategy and Surface Realization for Task-oriented Dialogues

no code implementations29 Sep 2021 Chenchen Ye, Lizi Liao, Fuli Feng, Wei Ji, Tat-Seng Chua

The core is to construct a latent content space for strategy optimization and disentangle the surface style from it.

Reinforcement Learning (RL) Style Transfer +1

MConv: An Environment for Multimodal Conversational Search across Multiple Domains

1 code implementation SIGIR 2021 Lizi Liao, Le Hong Long, Zheng Zhang, Minlie Huang, Tat-Seng Chua

Second, a set of benchmark results for dialogue state tracking, conversational recommendation, response generation as well as a unified model for multiple tasks are reported.

Conversational Search Dialogue State Tracking +1

Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting

1 code implementation25 May 2021 Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua, Jinyoung Moon, Hong-Han Shuai

This companion paper supports the replication of the fashion trend forecasting experiments with the KERN (Knowledge Enhanced Recurrent Network) method that we presented in the ICMR 2020.

Leveraging Multiple Relations for Fashion Trend Forecasting Based on Social Media

no code implementations7 May 2021 Yujuan Ding, Yunshan Ma, Lizi Liao, Wai Keung Wong, Tat-Seng Chua

Towards insightful fashion trend forecasting, previous work [1] proposed to analyze more fine-grained fashion elements which can informatively reveal fashion trends.

Time Series Analysis

Rethinking Dialogue State Tracking with Reasoning

no code implementations27 May 2020 Lizi Liao, Yunshan Ma, Wenqiang Lei, Tat-Seng Chua

Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management.

Dialogue Management Dialogue State Tracking +1

Knowledge Enhanced Neural Fashion Trend Forecasting

1 code implementation7 May 2020 Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua

Further-more, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge EnhancedRecurrent Network model (KERN) which takes advantage of the capability of deep recurrent neural networks in modeling time-series data.

Time Series Time Series Analysis

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

Who, Where, and What to Wear? Extracting Fashion Knowledge from Social Media

no code implementations12 Aug 2019 Yunshan Ma, Xun Yang, Lizi Liao, Yixin Cao, Tat-Seng Chua

We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata.

Human Detection

Automatic Fashion Knowledge Extraction from Social Media

no code implementations12 Aug 2019 Yunshan Ma, Lizi Liao, Tat-Seng Chua

Fashion knowledge plays a pivotal role in helping people in their dressing.

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

Neural Collaborative Filtering

43 code implementations WWW 2017 Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua

When it comes to model the key factor in collaborative filtering -- the interaction between user and item features, they still resorted to matrix factorization and applied an inner product on the latent features of users and items.

Collaborative Filtering Recommendation Systems

Attributed Social Network Embedding

1 code implementation14 May 2017 Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks.

Social and Information Networks

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