Search Results for author: Ying Shen

Found 61 papers, 25 papers with code

Amalgamating Knowledge from Two Teachers for Task-oriented Dialogue System with Adversarial Training

1 code implementation EMNLP 2020 Wanwei He, Min Yang, Rui Yan, Chengming Li, Ying Shen, Ruifeng Xu

Instead of adopting the classic student-teacher learning of forcing the output of a student network to exactly mimic the soft targets produced by the teacher networks, we introduce two discriminators as in generative adversarial network (GAN) to transfer knowledge from two teachers to the student.

Generative Adversarial Network Task-Oriented Dialogue Systems

Wasserstein Selective Transfer Learning for Cross-domain Text Mining

no code implementations EMNLP 2021 Lingyun Feng, Minghui Qiu, Yaliang Li, Haitao Zheng, Ying Shen

However, the source and target domains usually have different data distributions, which may lead to negative transfer.

Transfer Learning

Many-to-many Image Generation with Auto-regressive Diffusion Models

no code implementations3 Apr 2024 Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu

This paper introduces a domain-general framework for many-to-many image generation, capable of producing interrelated image series from a given set of images, offering a scalable solution that obviates the need for task-specific solutions across different multi-image scenarios.

Image Generation Novel View Synthesis

Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation

no code implementations3 Apr 2024 Zhe Xu, Daoyuan Chen, Jiayi Kuang, Zihao Yi, Yaliang Li, Ying Shen

Emotional Support Conversation (ESC) systems are pivotal in providing empathetic interactions, aiding users through negative emotional states by understanding and addressing their unique experiences.

Decoder Empathetic Response Generation +3

A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems

no code implementations28 Feb 2024 Zihao Yi, Jiarui Ouyang, YuWen Liu, Tianhao Liao, Zhe Xu, Ying Shen

This survey provides a comprehensive review of research on multi-turn dialogue systems, with a particular focus on multi-turn dialogue systems based on large language models (LLMs).

Multimodal Instruction Tuning with Conditional Mixture of LoRA

no code implementations24 Feb 2024 Ying Shen, Zhiyang Xu, Qifan Wang, Yu Cheng, Wenpeng Yin, Lifu Huang

Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in diverse tasks across different domains, with an increasing focus on improving their zero-shot generalization capabilities for unseen multimodal tasks.

Zero-shot Generalization

Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning

no code implementations18 Feb 2024 Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin, Yu Cheng, Qifan Wang, Lifu Huang

Despite vision-language models' (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking task diversity in pretraining and visual instruction tuning, and (2) annotation error and bias in GPT-4 synthesized instruction tuning data.

Hallucination Visual Question Answering

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models

no code implementations8 Feb 2024 Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen

The confluence of Federated Learning (FL) and Large Language Models (LLMs) is ushering in a new era in privacy-preserving natural language processing.

Federated Learning Privacy Preserving

Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study

no code implementations31 Jan 2024 Qirui Jiao, Daoyuan Chen, Yilun Huang, Yaliang Li, Ying Shen

Despite the impressive capabilities of Multimodal Large Language Models (MLLMs) in integrating text and image modalities, challenges remain in accurately interpreting detailed visual elements.

Hallucination object-detection +3

Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters

1 code implementation19 Nov 2023 Yinghui Li, Zishan Xu, Shaoshen Chen, Haojing Huang, Yangning Li, Yong Jiang, Zhongli Li, Qingyu Zhou, Hai-Tao Zheng, Ying Shen

To the best of our knowledge, Visual-C$^3$ is the first real-world visual and the largest human-crafted dataset for the Chinese character checking scenario.

X-Eval: Generalizable Multi-aspect Text Evaluation via Augmented Instruction Tuning with Auxiliary Evaluation Aspects

no code implementations15 Nov 2023 Minqian Liu, Ying Shen, Zhiyang Xu, Yixin Cao, Eunah Cho, Vaibhav Kumar, Reza Ghanadan, Lifu Huang

Natural Language Generation (NLG) typically involves evaluating the generated text in various aspects (e. g., consistency and naturalness) to obtain a comprehensive assessment.

Dialogue Generation Language Modelling +2

Tunable Soft Prompts are Messengers in Federated Learning

1 code implementation12 Nov 2023 Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li

As the global model itself is not required to be shared and the local training is conducted based on an auxiliary model with fewer parameters than the global model, the proposed approach provides protection for the global model while reducing communication and computation costs in FL.

Federated Learning Language Modelling +1

MULTISCRIPT: Multimodal Script Learning for Supporting Open Domain Everyday Tasks

1 code implementation8 Oct 2023 Jingyuan Qi, Minqian Liu, Ying Shen, Zhiyang Xu, Lifu Huang

Automatically generating scripts (i. e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI virtual assistants to guide humans to complete everyday tasks, especially unfamiliar ones.

Correct Like Humans: Progressive Learning Framework for Chinese Text Error Correction

no code implementations30 Jun 2023 Yinghui Li, Shirong Ma, Shaoshen Chen, Haojing Huang, Shulin Huang, Yangning Li, Hai-Tao Zheng, Ying Shen

During the training process, ProTEC guides the model to learn text error correction by incorporating these sub-tasks into a progressive paradigm.

Multi-Task Learning

LTCR: Long-Text Chinese Rumor Detection Dataset

1 code implementation12 Jun 2023 Ziyang Ma, Mengsha Liu, Guian Fang, Ying Shen

False information can spread quickly on social media, negatively influencing the citizens' behaviors and responses to social events.

Fake News Detection Misinformation

The Art of SOCRATIC QUESTIONING: Recursive Thinking with Large Language Models

1 code implementation24 May 2023 Jingyuan Qi, Zhiyang Xu, Ying Shen, Minqian Liu, Di Jin, Qifan Wang, Lifu Huang

Chain-of-Thought (CoT) prompting enables large language models to solve complex reasoning problems by generating intermediate steps.

Language Modelling Math +2

CLEME: Debiasing Multi-reference Evaluation for Grammatical Error Correction

2 code implementations18 May 2023 Jingheng Ye, Yinghui Li, Qingyu Zhou, Yangning Li, Shirong Ma, Hai-Tao Zheng, Ying Shen

Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging task due to its subjectivity.

Grammatical Error Correction

Counterfactual Debiasing for Generating Factually Consistent Text Summaries

no code implementations18 May 2023 Chenhe Dong, Yuexiang Xie, Yaliang Li, Ying Shen

Despite substantial progress in abstractive text summarization to generate fluent and informative texts, the factual inconsistency in the generated summaries remains an important yet challenging problem to be solved.

Abstractive Text Summarization counterfactual

From Retrieval to Generation: Efficient and Effective Entity Set Expansion

no code implementations7 Apr 2023 Shulin Huang, Shirong Ma, Yangning Li, Yinghui Li, Yong Jiang, Hai-Tao Zheng, Ying Shen

For efficiency, expansion time consumed by GenExpan is independent of entity vocabulary and corpus size, and GenExpan achieves an average 600% speedup compared to strong baselines.

Language Modelling Retrieval

Learning by Asking for Embodied Visual Navigation and Task Completion

1 code implementation9 Feb 2023 Ying Shen, Ismini Lourentzou

The research community has shown increasing interest in designing intelligent embodied agents that can assist humans in accomplishing tasks.

Question Answering Visual Navigation

MultiInstruct: Improving Multi-Modal Zero-Shot Learning via Instruction Tuning

1 code implementation21 Dec 2022 Zhiyang Xu, Ying Shen, Lifu Huang

Our results indicate that fine-tuning the model on a diverse set of tasks and instructions leads to a reduced sensitivity to variations in instructions for each task.

Transfer Learning Zero-Shot Learning

Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning

1 code implementation12 Dec 2022 Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li

In this study, we further broaden the application scope of FL in NLP by proposing an Assign-Then-Contrast (denoted as ATC) framework, which enables clients with heterogeneous NLP tasks to construct an FL course and learn useful knowledge from each other.

Federated Learning Natural Language Understanding +1

Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing Generation

1 code implementation29 Oct 2022 Shulin Huang, Shirong Ma, Yinghui Li, Yangning Li, Shiyang Lin, Hai-Tao Zheng, Ying Shen

Facing this dilemma, we focus on a novel CTG scenario, i. e., blessing generation which is challenging because high-quality blessing texts require CTG models to comprehensively consider the entanglement between multiple attributes (e. g., objects and occasions).

Attribute Text Generation

Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction

2 code implementations19 Oct 2022 Shirong Ma, Yinghui Li, Rongyi Sun, Qingyu Zhou, Shulin Huang, Ding Zhang, Li Yangning, Ruiyang Liu, Zhongli Li, Yunbo Cao, Haitao Zheng, Ying Shen

Extensive experiments and detailed analyses not only demonstrate that the training data constructed by our method effectively improves the performance of CGEC models, but also reflect that our benchmark is an excellent resource for further development of the CGEC field.

Grammatical Error Correction

Automatic Context Pattern Generation for Entity Set Expansion

1 code implementation17 Jul 2022 Yinghui Li, Shulin Huang, Xinwei Zhang, Qingyu Zhou, Yangning Li, Ruiyang Liu, Yunbo Cao, Hai-Tao Zheng, Ying Shen

In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities.

Information Retrieval Retrieval +1

Contrastive Learning with Hard Negative Entities for Entity Set Expansion

1 code implementation16 Apr 2022 Yinghui Li, Yangning Li, Yuxin He, Tianyu Yu, Ying Shen, Hai-Tao Zheng

In addition, we propose the ProbExpan, a novel probabilistic ESE framework utilizing the entity representation obtained by the aforementioned language model to expand entities.

Contrastive Learning Language Modelling

Automatic Depression Detection: An Emotional Audio-Textual Corpus and a GRU/BiLSTM-based Model

1 code implementation15 Feb 2022 Ying Shen, Huiyu Yang, Lin Lin

Depression is a global mental health problem, the worst case of which can lead to suicide.

Depression Detection

A Survey of Natural Language Generation

no code implementations22 Dec 2021 Chenhe Dong, Yinghui Li, Haifan Gong, Miaoxin Chen, Junxin Li, Ying Shen, Min Yang

This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-to-text generation deep learning methods, as well as new applications of NLG technology.

Data-to-Text Generation nlg evaluation

HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression

1 code implementation EMNLP 2021 Chenhe Dong, Yaliang Li, Ying Shen, Minghui Qiu

In this paper, we target to compress PLMs with knowledge distillation, and propose a hierarchical relational knowledge distillation (HRKD) method to capture both hierarchical and domain relational information.

Few-Shot Learning Knowledge Distillation +2

Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking

1 code implementation ACL 2021 Binzong Geng, Fajie Yuan, Qiancheng Xu, Ying Shen, Ruifeng Xu, Min Yang

This ability to learn consecutive tasks without forgetting how to perform previously trained problems is essential for developing an online dialogue system.

Continual Learning Network Pruning

Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge

no code implementations12 Apr 2021 Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen

Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge.

Answer Selection Representation Learning +1

Learning Purified Feature Representations from Task-irrelevant Labels

no code implementations22 Feb 2021 Yinghui Li, Chen Wang, Yangning Li, Hai-Tao Zheng, Ying Shen

Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks.

Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation

no code implementations20 Jan 2021 Lingyun Feng, Minghui Qiu, Yaliang Li, Hai-Tao Zheng, Ying Shen

Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications.

Knowledge Distillation

Answer-driven Deep Question Generation based on Reinforcement Learning

no code implementations COLING 2020 Liuyin Wang, Zihan Xu, Zibo Lin, Haitao Zheng, Ying Shen

First, we propose an answer-aware initialization module with a gated connection layer which introduces both document and answer information to the decoder, thus helping to guide the choice of answer-focused question words.

Decoder Question Generation +3

Integrating User History into Heterogeneous Graph for Dialogue Act Recognition

no code implementations COLING 2020 Dong Wang, Ziran Li, Haitao Zheng, Ying Shen

Dialogue Act Recognition (DAR) is a challenging problem in Natural Language Understanding, which aims to attach Dialogue Act (DA) labels to each utterance in a conversation.

Dialogue Act Classification

Summarize before Aggregate: A Global-to-local Heterogeneous Graph Inference Network for Conversational Emotion Recognition

no code implementations COLING 2020 Dongming Sheng, Dong Wang, Ying Shen, Haitao Zheng, Haozhuang Liu

Local dependencies, which captures short-term emotional effects between neighbouring utterances, are further injected via an Aggregation Graph to distinguish the subtle differences between utterances containing emotional phrases.

Emotion Recognition in Conversation

Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents

no code implementations ACL 2020 Daoyuan Chen, Yaliang Li, Kai Lei, Ying Shen

Distant supervision based methods for entity and relation extraction have received increasing popularity due to the fact that these methods require light human annotation efforts.

Relation Relation Extraction

A multi-agent ontologies-based clinical decision support system

no code implementations21 Jan 2020 Ying Shen, Jacquet-Andrieu Armelle, Joël Colloc

Our approach is based on the specialization of agents adapted to the knowledge models used during the clinical steps and ontologies.

Clinical Knowledge

Chinese Relation Extraction with Multi-Grained Information and External Linguistic Knowledge

1 code implementation ACL 2019 Ziran Li, Ning Ding, Zhiyuan Liu, Hai-Tao Zheng, Ying Shen

Chinese relation extraction is conducted using neural networks with either character-based or word-based inputs, and most existing methods typically suffer from segmentation errors and ambiguity of polysemy.

Relation Relation Extraction +1

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

2 code implementations6 Dec 2018 Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen

Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.

Answer Selection Knowledge Base Question Answering +2

Approach for Semi-automatic Construction of Anti-infective Drug Ontology Based on Entity Linking

no code implementations5 Dec 2018 Ying Shen, Yang Deng, Kaiqi Yuan, Li Liu, Yong liu

Experiments show that our selected features have achieved a precision rate of 86. 77%, a recall rate of 89. 03% and an F1 score of 87. 89%.

Entity Linking

MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs

no code implementations5 Dec 2018 Kai Lei, Kaiqi Yuan, Qiang Zhang, Ying Shen

We present MedSim, a novel semantic SIMilarity method based on public well-established bio-MEDical knowledge graphs (KGs) and large-scale corpus, to study the therapeutic substitution of antibiotics.

Knowledge Graphs Semantic Similarity +1

A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions

no code implementations5 Dec 2018 Kai Lei, Bing Zhang, Yong liu, Yang Deng, Dongyu Zhang, Ying Shen

In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.

Entity Linking Learning-To-Rank +5

Constructing Ontology-Based Cancer Treatment Decision Support System with Case-Based Reasoning

no code implementations5 Dec 2018 Ying Shen, Joël Colloc, Armelle Jacquet-Andrieu, Ziyi Guo, Yong liu

Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS).

General Classification

Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding

no code implementations5 Dec 2018 Ying Shen, Qiang Zhang, Jin Zhang, Jiyue Huang, Yuming Lu, Kai Lei

However, in electronic medical records (EMR), the texts containing sentences are shorter than that in general domain, which leads to the lack of semantic features and the ambiguity of semantic.

Clustering General Classification +3

MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data

no code implementations27 Sep 2018 Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei

In the light of these challenges, we propose a new truth discovery method, MedTruth, for medical knowledge condition discovery, which incorporates prior source quality information into the source reliability estimation procedure, and also utilizes the knowledge triple information for trustworthy information computation.


Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge

no code implementations COLING 2018 Yang Deng, Ying Shen, Min Yang, Yaliang Li, Nan Du, Wei Fan, Kai Lei

In this paper, we propose Knowledge-aware Attentive Network (KAN), a transfer learning framework for cross-domain answer selection, which uses the knowledge base as a bridge to enable knowledge transfer from the source domain to the target domains.

Answer Selection Information Retrieval +2

Cooperative Denoising for Distantly Supervised Relation Extraction

no code implementations COLING 2018 Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen

Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.

Denoising Information Retrieval +4

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