78 citations · 432 across the 28 of their papers we have counts for
28 papers
ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation
Bang Yang, Fenglin Liu, Yuexian Zou +3
Natural Language Generation (NLG) accepts input data in the form of images, videos, or text and generates corresponding natural language text as output. Existing NLG methods mainly…
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
Chenyu You, Weicheng Dai, Yifei Min +5
For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pa…
Aligning Source Visual and Target Language Domains for Unpaired Video Captioning
Fenglin Liu, Xian Wu, Chenyu You +3
Training supervised video captioning model requires coupled video-caption pairs. However, for many targeted languages, sufficient paired data are not available. To this end, we int…
Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations
Peng Jin, Jinfa Huang, Fenglin Liu +5
Most video-and-language representation learning approaches employ contrastive learning, e.g., CLIP, to project the video and text features into a common latent space according to t…
DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention
Fenglin Liu, Xian Wu, Shen Ge +4
Vision-and-language (V-L) tasks require the system to understand both vision content and natural language, thus learning fine-grained joint representations of vision and language (…
Retrieval-Augmented and Knowledge-Grounded Language Models for Faithful Clinical Medicine
Fenglin Liu, Bang Yang, Chenyu You +6
Language models (LMs), including large language models (such as ChatGPT), have the potential to assist clinicians in generating various clinical notes. However, LMs are prone to pr…
Prophet Attention: Predicting Attention with Future Attention for Image Captioning
Fenglin Liu, Xuancheng Ren, Xian Wu +3
Recently, attention based models have been used extensively in many sequence-to-sequence learning systems. Especially for image captioning, the attention based models are expected…
Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels
Chenyu You, Weicheng Dai, Fenglin Liu +6
Recent studies on contrastive learning have achieved remarkable performance solely by leveraging few labels in the context of medical image segmentation. Existing methods mainly fo…
Graph-in-Graph Network for Automatic Gene Ontology Description Generation
Fenglin Liu, Bang Yang, Chenyu You +4
Gene Ontology (GO) is the primary gene function knowledge base that enables computational tasks in biomedicine. The basic element of GO is a term, which includes a set of genes wit…
Competence-based Multimodal Curriculum Learning for Medical Report Generation
Fenglin Liu, Shen Ge, Yuexian Zou +1
Medical report generation task, which targets to produce long and coherent descriptions of medical images, has attracted growing research interests recently. Different from the gen…
End-to-end Spoken Conversational Question Answering: Task, Dataset and Model
Chenyu You, Nuo Chen, Fenglin Liu +3
In spoken question answering, the systems are designed to answer questions from contiguous text spans within the related speech transcripts. However, the most natural way that huma…
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation
Di You, Fenglin Liu, Shen Ge +3
Recently, medical report generation, which aims to automatically generate a long and coherent descriptive paragraph of a given medical image, has received growing research interest…
Class-Aware Adversarial Transformers for Medical Image Segmentation
Chenyu You, Ruihan Zhao, Fenglin Liu +5
Transformers have made remarkable progress towards modeling long-range dependencies within the medical image analysis domain. However, current transformer-based models suffer from…
Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation
Fenglin Liu, Chenyu You, Xian Wu +3
Medical report generation, which aims to automatically generate a long and coherent report of a given medical image, has been receiving growing research interests. Existing approac…
O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning
Fenglin Liu, Xuancheng Ren, Xian Wu +4
Video captioning combines video understanding and language generation. Different from image captioning that describes a static image with details of almost every object, video capt…
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model
Zhiqi Huang, Fenglin Liu, Xian Wu +4
While Machine Comprehension (MC) has attracted extensive research interests in recent years, existing approaches mainly belong to the category of Machine Reading Comprehension task…
Exploring and Distilling Posterior and Prior Knowledge for Radiology Report Generation
Fenglin Liu, Xian Wu, Shen Ge +2
Automatically generating radiology reports can improve current clinical practice in diagnostic radiology. On one hand, it can relieve radiologists from the heavy burden of report w…
Exploring Semantic Relationships for Unpaired Image Captioning
Fenglin Liu, Meng Gao, Tianhao Zhang +1
Recently, image captioning has aroused great interest in both academic and industrial worlds. Most existing systems are built upon large-scale datasets consisting of image-sentence…
Contrastive Attention for Automatic Chest X-ray Report Generation
Fenglin Liu, Changchang Yin, Xian Wu +4
Recently, chest X-ray report generation, which aims to automatically generate descriptions of given chest X-ray images, has received growing research interests. The key challenge o…
Rethinking Skip Connection with Layer Normalization in Transformers and ResNets
Fenglin Liu, Xuancheng Ren, Zhiyuan Zhang +2
Skip connection, is a widely-used technique to improve the performance and the convergence of deep neural networks, which is believed to relieve the difficulty in optimization due…
Adaptive Bi-directional Attention: Exploring Multi-Granularity Representations for Machine Reading Comprehension
Nuo Chen, Fenglin Liu, Chenyu You +2
Recently, the attention-enhanced multi-layer encoder, such as Transformer, has been extensively studied in Machine Reading Comprehension (MRC). To predict the answer, it is common…
Towards Data Distillation for End-to-end Spoken Conversational Question Answering
Chenyu You, Nuo Chen, Fenglin Liu +2
In spoken question answering, QA systems are designed to answer questions from contiguous text spans within the related speech transcripts. However, the most natural way that human…
PIN: A Novel Parallel Interactive Network for Spoken Language Understanding
Peilin Zhou, Zhiqi Huang, Fenglin Liu +1
Spoken Language Understanding (SLU) is an essential part of the spoken dialogue system, which typically consists of intent detection (ID) and slot filling (SF) tasks. Recently, rec…
Rethinking and Improving Natural Language Generation with Layer-Wise Multi-View Decoding
Fenglin Liu, Xuancheng Ren, Guangxiang Zhao +4
In sequence-to-sequence learning, e.g., natural language generation, the decoder relies on the attention mechanism to efficiently extract information from the encoder. While it is…