215 citations · 521 across the 21 of their papers we have counts for
21 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…
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…
DeltaNet:Conditional Medical Report Generation for COVID-19 Diagnosis
Xian Wu, Shuxin Yang, Zhaopeng Qiu +6
Fast screening and diagnosis are critical in COVID-19 patient treatment. In addition to the gold standard RT-PCR, radiological imaging like X-ray and CT also works as an important…
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…
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…
Radiology Report Generation with a Learned Knowledge Base and Multi-modal Alignment
Shuxin Yang, Xian Wu, Shen Ge +2
In clinics, a radiology report is crucial for guiding a patient's treatment. However, writing radiology reports is a heavy burden for radiologists. To this end, we present an autom…
Knowledge Matters: Radiology Report Generation with General and Specific Knowledge
Shuxin Yang, Xian Wu, Shen Ge +2
Automatic radiology report generation is critical in clinics which can relieve experienced radiologists from the heavy workload and remind inexperienced radiologists of misdiagnosi…
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…
Towards Joint Intent Detection and Slot Filling via Higher-order Attention
Dongsheng Chen, Zhiqi Huang, Xian Wu +2
Intent detection (ID) and Slot filling (SF) are two major tasks in spoken language understanding (SLU). Recently, attention mechanism has been shown to be effective in jointly opti…
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…
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…
Automatic Distractor Generation for Multiple Choice Questions in Standard Tests
Zhaopeng Qiu, Xian Wu, Wei Fan
To assess the knowledge proficiency of a learner, multiple choice question is an efficient and widespread form in standard tests. However, the composition of the multiple choice qu…
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…
Multi-Grained Named Entity Recognition
Congying Xia, Chenwei Zhang, Tao Yang +6
This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totall…