Search Results for author: Wenjie Li

Found 123 papers, 45 papers with code

Effect Generation Based on Causal Reasoning

no code implementations Findings (EMNLP) 2021 Feiteng Mu, Wenjie Li, Zhipeng Xie

Given an input cause sentence, a causal subgraph is retrieved from the event causality network and is encoded with the graph attention mechanism, in order to support better reasoning of the potential effects.

Graph Attention Sentence

MMCoQA: Conversational Question Answering over Text, Tables, and Images

1 code implementation ACL 2022 Yongqi Li, Wenjie Li, Liqiang Nie

In this paper, we hence define a novel research task, i. e., multimodal conversational question answering (MMCoQA), aiming to answer users’ questions with multimodal knowledge sources via multi-turn conversations.

Benchmarking Conversational Question Answering +1

Event Graph based Sentence Fusion

no code implementations EMNLP 2021 Ruifeng Yuan, Zili Wang, Wenjie Li

Sentence fusion is a conditional generation task that merges several related sentences into a coherent one, which can be deemed as a summary sentence.

Abstractive Text Summarization Sentence +2

ICON: Improving Inter-Report Consistency of Radiology Report Generation via Lesion-aware Mix-up Augmentation

1 code implementation20 Feb 2024 Wenjun Hou, Yi Cheng, Kaishuai Xu, Yan Hu, Wenjie Li, Jiang Liu

Previous research on radiology report generation has made significant progress in terms of increasing the clinical accuracy of generated reports.

Medical Report Generation

Distillation Enhanced Generative Retrieval

no code implementations16 Feb 2024 Yongqi Li, Zhen Zhang, Wenjie Wang, Liqiang Nie, Wenjie Li, Tat-Seng Chua

Generative retrieval is a promising new paradigm in text retrieval that generates identifier strings of relevant passages as the retrieval target.

Retrieval Text Retrieval

Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond

no code implementations16 Feb 2024 Yongqi Li, Wenjie Wang, Leigang Qu, Liqiang Nie, Wenjie Li, Tat-Seng Chua

Building upon this capability, we propose to enable multimodal large language models (MLLMs) to memorize and recall images within their parameters.

Cross-Modal Retrieval Retrieval

Instruct Once, Chat Consistently in Multiple Rounds: An Efficient Tuning Framework for Dialogue

no code implementations10 Feb 2024 Jian Wang, Chak Tou Leong, Jiashuo Wang, Dongding Lin, Wenjie Li, Xiao-Yong Wei

Tuning pretrained language models for dialogue generation has been a prevalent paradigm for building capable dialogue agents.

Dialogue Generation

Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding

1 code implementation15 Jan 2024 Heming Xia, Zhe Yang, Qingxiu Dong, Peiyi Wang, Yongqi Li, Tao Ge, Tianyu Liu, Wenjie Li, Zhifang Sui

To mitigate the high inference latency stemming from autoregressive decoding in Large Language Models (LLMs), Speculative Decoding has emerged as a novel decoding paradigm for LLM inference.

Language Modelling Large Language Model

Mitigating Unhelpfulness in Emotional Support Conversations with Multifaceted AI Feedback

no code implementations11 Jan 2024 Jiashuo Wang, Chunpu Xu, Chak Tou Leong, Wenjie Li, Jing Li

An emotional support conversation system aims to alleviate users' emotional distress and assist them in addressing their challenges.

Contrastive Learning

The Critique of Critique

1 code implementation9 Jan 2024 Shichao Sun, Junlong Li, Weizhe Yuan, Ruifeng Yuan, Wenjie Li, PengFei Liu

In this paper, we pioneer the critique of critique, termed MetaCritique, which is a framework to evaluate the critique from two aspects, i. e., factuality as precision score and comprehensiveness as recall score.

Question Answering

How Far Are We from Believable AI Agents? A Framework for Evaluating the Believability of Human Behavior Simulation

1 code implementation28 Dec 2023 Yang Xiao, Yi Cheng, Jinlan Fu, Jiashuo Wang, Wenjie Li, PengFei Liu

Human behavior simulation of AI agents necessitates the agents to possess a quality of believability, which is crucial as it facilitates users in establishing trust toward the agents and streamlines the fulfillment of the agents' goal.

Language Modelling Large Language Model

Evolving Large Language Model Assistant with Long-Term Conditional Memory

no code implementations22 Dec 2023 Ruifeng Yuan, Shichao Sun, Zili Wang, Ziqiang Cao, Wenjie Li

It focuses on preserving the knowledge and experience from the history dialogue between the user and AI assistant, which can be applied to future dialogue for generating a better response.

Language Modelling Large Language Model +1

COOPER: Coordinating Specialized Agents towards a Complex Dialogue Goal

1 code implementation19 Dec 2023 Yi Cheng, Wenge Liu, Jian Wang, Chak Tou Leong, Yi Ouyang, Wenjie Li, Xian Wu, Yefeng Zheng

In recent years, there has been a growing interest in exploring dialogues with more complex goals, such as negotiation, persuasion, and emotional support, which go beyond traditional service-focused dialogue systems.

KBioXLM: A Knowledge-anchored Biomedical Multilingual Pretrained Language Model

1 code implementation20 Nov 2023 Lei Geng, Xu Yan, Ziqiang Cao, Juntao Li, Wenjie Li, Sujian Li, Xinjie Zhou, Yang Yang, Jun Zhang

We achieve a biomedical multilingual corpus by incorporating three granularity knowledge alignments (entity, fact, and passage levels) into monolingual corpora.

Relation XLM-R

Personalized Federated X -armed Bandit

no code implementations25 Oct 2023 Wenjie Li, Qifan Song, Jean Honorio

In this work, we study the personalized federated $\mathcal{X}$-armed bandit problem, where the heterogeneous local objectives of the clients are optimized simultaneously in the federated learning paradigm.

Federated Learning

RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning

1 code implementation21 Oct 2023 Wenjun Hou, Yi Cheng, Kaishuai Xu, Wenjie Li, Jiang Liu

It then combines the historical records, spatiotemporal information, and radiographs for report generation, where a disease progression graph and dynamic progression reasoning mechanism are devised to accurately select the attributes of each observation and progression.

Medical Report Generation

VIBE: Topic-Driven Temporal Adaptation for Twitter Classification

no code implementations16 Oct 2023 Yuji Zhang, Jing Li, Wenjie Li

Language features are evolving in real-world social media, resulting in the deteriorating performance of text classification in dynamics.

text-classification Text Classification

Self-Detoxifying Language Models via Toxification Reversal

1 code implementation14 Oct 2023 Chak Tou Leong, Yi Cheng, Jiashuo Wang, Jian Wang, Wenjie Li

Drawing on this idea, we devise a method to identify the toxification direction from the normal generation process to the one prompted with the negative prefix, and then steer the generation to the reversed direction by manipulating the information movement within the attention layers.

Language Modelling

Target-oriented Proactive Dialogue Systems with Personalization: Problem Formulation and Dataset Curation

1 code implementation11 Oct 2023 Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, Wenjie Li

Target-oriented dialogue systems, designed to proactively steer conversations toward predefined targets or accomplish specific system-side goals, are an exciting area in conversational AI.

Aligning Language Models with Human Preferences via a Bayesian Approach

1 code implementation NeurIPS 2023 Jiashuo Wang, Haozhao Wang, Shichao Sun, Wenjie Li

For this alignment, current popular methods leverage a reinforcement learning (RL) approach with a reward model trained on feedback from humans.

Contrastive Learning Reinforcement Learning (RL) +1

Learning to Rank in Generative Retrieval

2 code implementations27 Jun 2023 Yongqi Li, Nan Yang, Liang Wang, Furu Wei, Wenjie Li

However, only learning to generate is insufficient for generative retrieval.

Learning-To-Rank Passage Ranking +3

ORGAN: Observation-Guided Radiology Report Generation via Tree Reasoning

1 code implementation10 Jun 2023 Wenjun Hou, Kaishuai Xu, Yi Cheng, Wenjie Li, Jiang Liu

This paper explores the task of radiology report generation, which aims at generating free-text descriptions for a set of radiographs.

Medical Report Generation

Medical Dialogue Generation via Dual Flow Modeling

1 code implementation29 May 2023 Kaishuai Xu, Wenjun Hou, Yi Cheng, Jian Wang, Wenjie Li

It extracts the medical entities and dialogue acts used in the dialogue history and models their transitions with an entity-centric graph flow and a sequential act flow, respectively.

Dialogue Generation Dialogue Understanding

Multiview Identifiers Enhanced Generative Retrieval

1 code implementation26 May 2023 Yongqi Li, Nan Yang, Liang Wang, Furu Wei, Wenjie Li

Instead of simply matching a query to pre-existing passages, generative retrieval generates identifier strings of passages as the retrieval target.


Theoretically Principled Federated Learning for Balancing Privacy and Utility

no code implementations24 May 2023 Xiaojin Zhang, Wenjie Li, Kai Chen, Shutao Xia, Qiang Yang

We propose a general learning framework for the protection mechanisms that protects privacy via distorting model parameters, which facilitates the trade-off between privacy and utility.

Federated Learning

Dialogue Planning via Brownian Bridge Stochastic Process for Goal-directed Proactive Dialogue

1 code implementation9 May 2023 Jian Wang, Dongding Lin, Wenjie Li

The key to achieving this task lies in planning dialogue paths that smoothly and coherently direct conversations towards the target.

Dialogue Generation

CoVLR: Coordinating Cross-Modal Consistency and Intra-Modal Structure for Vision-Language Retrieval

no code implementations15 Apr 2023 Yang Yang, Zhongtian Fu, Xiangyu Wu, Wenjie Li

To address this challenge, in this paper, we experimentally observe that the vision-language divergence may cause the existence of strong and weak modalities, and the hard cross-modal consistency cannot guarantee that strong modal instances' relationships are not affected by weak modality, resulting in the strong modal instances' relationships perturbed despite learned consistent representations. To this end, we propose a novel and directly Coordinated VisionLanguage Retrieval method (dubbed CoVLR), which aims to study and alleviate the desynchrony problem between the cross-modal alignment and single-modal cluster-preserving tasks.

Cross-Modal Retrieval Instance Search +1

A Game-theoretic Framework for Privacy-preserving Federated Learning

no code implementations11 Apr 2023 Xiaojin Zhang, Lixin Fan, Siwei Wang, Wenjie Li, Kai Chen, Qiang Yang

To address this, we propose the first game-theoretic framework that considers both FL defenders and attackers in terms of their respective payoffs, which include computational costs, FL model utilities, and privacy leakage risks.

Federated Learning Privacy Preserving

PyXAB -- A Python Library for $\mathcal{X}$-Armed Bandit and Online Blackbox Optimization Algorithms

1 code implementation7 Mar 2023 Wenjie Li, Haoze Li, Jean Honorio, Qifan Song

We introduce a Python open-source library for $\mathcal{X}$-armed bandit and online blackbox optimization named PyXAB.

Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization

1 code implementation24 Feb 2023 Shichao Sun, Ruifeng Yuan, Wenjie Li, Sujian Li

Unsupervised extractive summarization aims to extract salient sentences from a document as the summary without labeled data.

Contrastive Learning Extractive Summarization +3

Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network

no code implementations29 Dec 2022 Wenjie Li, Juncheng Li, Guangwei Gao, Weihong Deng, Jian Yang, Guo-Jun Qi, Chia-Wen Lin

Recently, great progress has been made in single-image super-resolution (SISR) based on deep learning technology.

Image Super-Resolution

COLA: Improving Conversational Recommender Systems by Collaborative Augmentation

no code implementations15 Dec 2022 Dongding Lin, Jian Wang, Wenjie Li

Inspired by collaborative filtering, we propose a collaborative augmentation (COLA) method to simultaneously improve both item representation learning and user preference modeling to address these issues.

CoLA Collaborative Filtering +2

Few-shot Query-Focused Summarization with Prefix-Merging

no code implementations29 Nov 2022 Ruifeng Yuan, Zili Wang, Ziqiang Cao, Wenjie Li

Drawn inspiration from prefix-tuning, we are allowed to integrate the task knowledge from text summarization and question answering into a properly designed prefix and apply the merged prefix to query-focused summarization.

Few-Shot Learning Query-focused Summarization +2

Always Valid Risk Monitoring for Online Matrix Completion

no code implementations18 Nov 2022 Chi-Hua Wang, Wenjie Li

Always-valid concentration inequalities are increasingly used as performance measures for online statistical learning, notably in the learning of generative models and supervised learning.

Matrix Completion valid

CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation

1 code implementation1 Nov 2022 Jiashuo Wang, Yi Cheng, Wenjie Li

Recent approaches to empathetic response generation incorporate emotion causalities to enhance comprehension of both the user's feelings and experiences.

Empathetic Response Generation Graph Generation +1

Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning

1 code implementation9 Oct 2022 Yi Cheng, Wenge Liu, Wenjie Li, Jiashuo Wang, Ruihui Zhao, Bang Liu, Xiaodan Liang, Yefeng Zheng

Providing Emotional Support (ES) to soothe people in emotional distress is an essential capability in social interactions.

Dialogue Generation

Vertical Semi-Federated Learning for Efficient Online Advertising

no code implementations30 Sep 2022 Wenjie Li, Qiaolin Xia, Hao Cheng, Kouyin Xue, Shu-Tao Xia

Specifically, we build an inference-efficient single-party student model applicable to the whole sample space and meanwhile maintain the advantage of the federated feature extension.

Federated Learning

Modeling Content-Emotion Duality via Disentanglement for Empathetic Conversation

1 code implementation26 Sep 2022 Peiqin Lin, Jiashuo Wang, Hinrich Schütze, Wenjie Li

To solve the task, it is essential to model the content-emotion duality of a dialogue, which is composed of the content view (i. e., what personal experiences are described) and the emotion view (i. e., the feelings of the speaker on these experiences).

Disentanglement Empathetic Response Generation +1

Visual Subtitle Feature Enhanced Video Outline Generation

no code implementations24 Aug 2022 Qi Lv, Ziqiang Cao, Wenrui Xie, Derui Wang, Jingwen Wang, Zhiwei Hu, Tangkun Zhang, Ba Yuan, Yuanhang Li, Min Cao, Wenjie Li, Sujian Li, Guohong Fu

Furthermore, based on the similarity between video outlines and textual outlines, we use a large number of articles with chapter headings to pretrain our model.

Headline Generation Navigate +4

Addressing Token Uniformity in Transformers via Singular Value Transformation

1 code implementation24 Aug 2022 Hanqi Yan, Lin Gui, Wenjie Li, Yulan He

In this paper, we propose to use the distribution of singular values of outputs of each transformer layer to characterise the phenomenon of token uniformity and empirically illustrate that a less skewed singular value distribution can alleviate the `token uniformity' problem.

Semantic Textual Similarity

Revising Image-Text Retrieval via Multi-Modal Entailment

no code implementations22 Aug 2022 Xu Yan, Chunhui Ai, Ziqiang Cao, Min Cao, Sujian Li, Wenjie Li, Guohong Fu

While the builders of existing image-text retrieval datasets strive to ensure that the caption matches the linked image, they cannot prevent a caption from fitting other images.

Natural Language Inference Retrieval +2

Follow Me: Conversation Planning for Target-driven Recommendation Dialogue Systems

1 code implementation6 Aug 2022 Jian Wang, Dongding Lin, Wenjie Li

Recommendation dialogue systems aim to build social bonds with users and provide high-quality recommendations.

Dialogue Generation

Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution

1 code implementation6 Jul 2022 Wenjie Li, Juncheng Li, Guangwei Gao, Jiantao Zhou, Jian Yang, Guo-Jun Qi

Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction.

Image Super-Resolution

VFed-SSD: Towards Practical Vertical Federated Advertising

no code implementations31 May 2022 Wenjie Li, Qiaolin Xia, Junfeng Deng, Hao Cheng, Jiangming Liu, Kouying Xue, Yong Cheng, Shu-Tao Xia

As an emerging secure learning paradigm in lever-aging cross-agency private data, vertical federatedlearning (VFL) is expected to improve advertising models by enabling the joint learning of complementary user attributes privately owned by the advertiser and the publisher.

Federated Learning Knowledge Distillation +1

Federated X-Armed Bandit

1 code implementation30 May 2022 Wenjie Li, Qifan Song, Jean Honorio, Guang Lin

This work establishes the first framework of federated $\mathcal{X}$-armed bandit, where different clients face heterogeneous local objective functions defined on the same domain and are required to collaboratively figure out the global optimum.

A Coupling Enhancement Algorithm for ZrO2 Ceramic Bearing Ball Surface Defect Detection Based on Cartoon-texture Decomposition Model and Multi-Scale Filtering Method

no code implementations23 May 2022 Wei Wang, Xin Zhang, Jiaqi Yi, Xianqi Liao, Wenjie Li, Zhenhong Li

The experimental results show that the image denoising method of ZrO2 ceramic bearing ball surface defect based on cartoon-texture decomposition model can denoise while retaining the image details.

Defect Detection Image Denoising +1

Federated Online Sparse Decision Making

no code implementations27 Feb 2022 Chi-Hua Wang, Wenjie Li, Guang Cheng, Guang Lin

This paper presents a novel federated linear contextual bandits model, where individual clients face different K-armed stochastic bandits with high-dimensional decision context and coupled through common global parameters.

Decision Making Multi-Armed Bandits

Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution

1 code implementation16 Dec 2021 Guangwei Gao, Wenjie Li, Juncheng Li, Fei Wu, Huimin Lu, Yi Yu

Convolutional neural networks based single-image super-resolution (SISR) has made great progress in recent years.

Image Super-Resolution

Deep Dirichlet Process Mixture Models

no code implementations29 Sep 2021 Naiqi Li, Wenjie Li, Yong Jiang, Shu-Tao Xia

In this paper we propose the deep Dirichlet process mixture (DDPM) model, which is an unsupervised method that simultaneously performs clustering and feature learning.


Alleviating Exposure Bias via Contrastive Learning for Abstractive Text Summarization

1 code implementation26 Aug 2021 Shichao Sun, Wenjie Li

During the training stage, with teacher forcing these models are optimized to maximize the likelihood of the gold summary given the gold summary tokens as input to the decoder, while at inference the given tokens are replaced by the generated tokens.

Abstractive Text Summarization Contrastive Learning

PolyU CBS-Comp at SemEval-2021 Task 1: Lexical Complexity Prediction (LCP)

no code implementations SEMEVAL 2021 Rong Xiang, Jinghang Gu, Emmanuele Chersoni, Wenjie Li, Qin Lu, Chu-Ren Huang

In this contribution, we describe the system presented by the PolyU CBS-Comp Team at the Task 1 of SemEval 2021, where the goal was the estimation of the complexity of words in a given sentence context.

Lexical Complexity Prediction Sentence +1

Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization

1 code implementation17 Jun 2021 Wenjie Li, Chi-Hua Wang, Guang Cheng, Qifan Song

In this paper, we make the key delineation on the roles of resolution and statistical uncertainty in hierarchical bandits-based black-box optimization algorithms, guiding a more general analysis and a more efficient algorithm design.

A Graph-guided Multi-round Retrieval Method for Conversational Open-domain Question Answering

no code implementations17 Apr 2021 Yongqi Li, Wenjie Li, Liqiang Nie

Moreover, in order to collect more complementary information in the historical context, we also propose to incorporate the multi-round relevance feedback technique to explore the impact of the retrieval context on current question understanding.

Conversational Question Answering Open-Domain Question Answering +1

Data Distillation for Text Classification

2 code implementations17 Apr 2021 Yongqi Li, Wenjie Li

In this paper, we study a related but orthogonal issue, data distillation, which aims to distill the knowledge from a large training dataset down to a smaller and synthetic one.

General Classification text-classification +1

A Simple Unified Framework for High Dimensional Bandit Problems

no code implementations18 Feb 2021 Wenjie Li, Adarsh Barik, Jean Honorio

Stochastic high dimensional bandit problems with low dimensional structures are useful in different applications such as online advertising and drug discovery.

Drug Discovery Vocal Bursts Intensity Prediction

Incremental Knowledge Based Question Answering

no code implementations18 Jan 2021 Yongqi Li, Wenjie Li, Liqiang Nie

In the past years, Knowledge-Based Question Answering (KBQA), which aims to answer natural language questions using facts in a knowledge base, has been well developed.

Incremental Learning Knowledge Distillation +1

On the Marginal Regret Bound Minimization of Adaptive Methods

no code implementations1 Jan 2021 Wenjie Li, Guang Cheng

Numerous adaptive algorithms such as AMSGrad and Radam have been proposed and applied to deep learning recently.

Open-Ended Question Answering

Variance Reduction on General Adaptive Stochastic Mirror Descent

no code implementations26 Dec 2020 Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng

In this work, we investigate the idea of variance reduction by studying its properties with general adaptive mirror descent algorithms in nonsmooth nonconvex finite-sum optimization problems.

Stochastic Deep Gaussian Processes over Graphs

1 code implementation NeurIPS 2020 Naiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia

In this paper we propose Stochastic Deep Gaussian Processes over Graphs (DGPG), which are deep structure models that learn the mappings between input and output signals in graph domains.

Gaussian Processes Variational Inference

Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT

1 code implementation COLING 2020 Ruifeng Yuan, Zili Wang, Wenjie Li

We also introduce a hierarchical structure, which incorporates the multi-level of granularities of the textual information into the model.

Extractive Summarization Natural Language Understanding +1

MedDG: An Entity-Centric Medical Consultation Dataset for Entity-Aware Medical Dialogue Generation

1 code implementation15 Oct 2020 Wenge Liu, Jianheng Tang, Yi Cheng, Wenjie Li, Yefeng Zheng, Xiaodan Liang

To push forward the future research on building expert-sensitive medical dialogue system, we proposes two kinds of medical dialogue tasks based on MedDG dataset.

Dialogue Generation Response Generation +1

Improving Accent Conversion with Reference Encoder and End-To-End Text-To-Speech

no code implementations19 May 2020 Wenjie Li, Benlai Tang, Xiang Yin, Yushi Zhao, Wei Li, Kang Wang, Hao Huang, Yuxuan Wang, Zejun Ma

Accent conversion (AC) transforms a non-native speaker's accent into a native accent while maintaining the speaker's voice timbre.

Increased-confidence adversarial examples for deep learning counter-forensics

no code implementations12 May 2020 Wenjie Li, Benedetta Tondi, Rongrong Ni, Mauro Barni

Transferability of adversarial examples is a key issue to apply this kind of attacks against multimedia forensics (MMF) techniques based on Deep Learning (DL) in a real-life setting.

Image Forensics

AdaX: Adaptive Gradient Descent with Exponential Long Term Memory

1 code implementation21 Apr 2020 Wenjie Li, Zhaoyang Zhang, Xinjiang Wang, Ping Luo

Although adaptive optimization algorithms such as Adam show fast convergence in many machine learning tasks, this paper identifies a problem of Adam by analyzing its performance in a simple non-convex synthetic problem, showing that Adam's fast convergence would possibly lead the algorithm to local minimums.

How Does BN Increase Collapsed Neural Network Filters?

no code implementations30 Jan 2020 Sheng Zhou, Xinjiang Wang, Ping Luo, Litong Feng, Wenjie Li, Wei zhang

This phenomenon is caused by the normalization effect of BN, which induces a non-trainable region in the parameter space and reduces the network capacity as a result.

object-detection Object Detection

Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization

no code implementations ACL 2019 Hai Ye, Wenjie Li, Lu Wang

Semantic parsing aims to transform natural language (NL) utterances into formal meaning representations (MRs), whereas an NL generator achieves the reverse: producing a NL description for some given MRs.

Code Generation Dialogue Management +2

Knowledge Graph Convolutional Networks for Recommender Systems

8 code implementations18 Mar 2019 Hongwei Wang, Miao Zhao, Xing Xie, Wenjie Li, Minyi Guo

To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these additional information.

Click-Through Rate Prediction Collaborative Filtering +3

When Collaborative Filtering Meets Reinforcement Learning

no code implementations2 Feb 2019 Yu Lei, Wenjie Li

In this paper, we study a multi-step interactive recommendation problem, where the item recommended at current step may affect the quality of future recommendations.

Collaborative Filtering reinforcement-learning +1

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

3 code implementations23 Jan 2019 Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo

Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems.

Collaborative Filtering Knowledge Graph Embedding +4

Visual-Texual Emotion Analysis with Deep Coupled Video and Danmu Neural Networks

no code implementations19 Nov 2018 Chenchen Li, Jialin Wang, Hongwei Wang, Miao Zhao, Wenjie Li, Xiaotie Deng

To enhance the emotion discriminativeness of words in textual feature extraction, we propose Emotional Word Embedding (EWE) to learn text representations by jointly considering their semantics and emotions.

Emotion Recognition MULTI-VIEW LEARNING

Incorporating Relevant Knowledge in Context Modeling and Response Generation

no code implementations9 Nov 2018 Yan-ran Li, Wenjie Li, Ziqiang Cao, Chengyao Chen

To sustain engaging conversation, it is critical for chatbots to make good use of relevant knowledge.

Attribute Chatbot +1

Meta-path Augmented Response Generation

no code implementations2 Nov 2018 Yan-ran Li, Wenjie Li

We propose a chatbot, namely Mocha to make good use of relevant entities when generating responses.

Chatbot Response Generation

Variational Autoregressive Decoder for Neural Response Generation

no code implementations EMNLP 2018 Jiachen Du, Wenjie Li, Yulan He, Ruifeng Xu, Lidong Bing, Xuan Wang

Combining the virtues of probability graphic models and neural networks, Conditional Variational Auto-encoder (CVAE) has shown promising performance in applications such as response generation.

Response Generation

NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation

no code implementations EMNLP 2018 Hui Su, Xiaoyu Shen, Wenjie Li, Dietrich Klakow

Sequence-to-Sequence (seq2seq) models have become overwhelmingly popular in building end-to-end trainable dialogue systems.

Dialogue Generation

Large scale classification in deep neural network with Label Mapping

no code implementations7 Jun 2018 Qizhi Zhang, Kuang-Chih Lee, Hongying Bao, Yuan You, Wenjie Li, Dongbai Guo

Therefore, it is infeasible to solve the multi-class classification problem using deep neural network when the number of classes are huge.

BIG-bench Machine Learning Classification +2

RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

9 code implementations9 Mar 2018 Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, Wenjie Li, Xing Xie, Minyi Guo

To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance.

Click-Through Rate Prediction Collaborative Filtering +2

Faithful to the Original: Fact Aware Neural Abstractive Summarization

no code implementations13 Nov 2017 Ziqiang Cao, Furu Wei, Wenjie Li, Sujian Li

While previous abstractive summarization approaches usually focus on the improvement of informativeness, we argue that faithfulness is also a vital prerequisite for a practical abstractive summarization system.

Abstractive Text Summarization Extractive Summarization +3

DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

13 code implementations IJCNLP 2017 Yan-ran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, Shuzi Niu

We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects.

Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

no code implementations26 Feb 2017 Tong Che, Yan-ran Li, Ruixiang Zhang, R. Devon Hjelm, Wenjie Li, Yangqiu Song, Yoshua Bengio

Despite the successes in capturing continuous distributions, the application of generative adversarial networks (GANs) to discrete settings, like natural language tasks, is rather restricted.

Mode Regularized Generative Adversarial Networks

no code implementations7 Dec 2016 Tong Che, Yan-ran Li, Athul Paul Jacob, Yoshua Bengio, Wenjie Li

Although Generative Adversarial Networks achieve state-of-the-art results on a variety of generative tasks, they are regarded as highly unstable and prone to miss modes.

Content-based Influence Modeling for Opinion Behavior Prediction

no code implementations COLING 2016 Chengyao Chen, Zhitao Wang, Yu Lei, Wenjie Li

The advantages of the proposed model is the ability to handle the semantic information and to learn two influence components including the opinion influence of the content information and the social relation factors.

Joint Copying and Restricted Generation for Paraphrase

no code implementations28 Nov 2016 Ziqiang Cao, Chuwei Luo, Wenjie Li, Sujian Li

In this paper, we develop a novel Seq2Seq model to fuse a copying decoder and a restricted generative decoder.

Abstractive Text Summarization Informativeness +2

Improving Multi-Document Summarization via Text Classification

no code implementations28 Nov 2016 Ziqiang Cao, Wenjie Li, Sujian Li, Furu Wei

Developed so far, multi-document summarization has reached its bottleneck due to the lack of sufficient training data and diverse categories of documents.

Document Summarization General Classification +3

Emotion Corpus Construction Based on Selection from Hashtags

no code implementations LREC 2016 Minglei Li, Yunfei Long, Lu Qin, Wenjie Li

Secondly, a SVM based classifier is used to select the data whose natural labels are consistent with the predicted labels.

Emotion Classification

Component-Enhanced Chinese Character Embeddings

no code implementations EMNLP 2015 Yan-ran Li, Wenjie Li, Fei Sun, Sujian Li

Distributed word representations are very useful for capturing semantic information and have been successfully applied in a variety of NLP tasks, especially on English.

General Classification text-classification +3

A Confident Information First Principle for Parametric Reduction and Model Selection of Boltzmann Machines

no code implementations5 Feb 2015 Xiaozhao Zhao, Yuexian Hou, Dawei Song, Wenjie Li

We then revisit Boltzmann machines (BM) from a model selection perspective and theoretically show that both the fully visible BM (VBM) and the BM with hidden units can be derived from the general binary multivariate distribution using the CIF principle.

Density Estimation Dimensionality Reduction +1

Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle

no code implementations16 Feb 2013 Xiaozhao Zhao, Yuexian Hou, Qian Yu, Dawei Song, Wenjie Li

Typical dimensionality reduction methods focus on directly reducing the number of random variables while retaining maximal variations in the data.

Density Estimation Dimensionality Reduction

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