637 citations · 875 across the 23 of their papers we have counts for
24 papers
Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning
Xiang Yuan, Gong Cheng, Kebing Yan +2
The past few years have witnessed the immense success of object detection, while current excellent detectors struggle on tackling size-limited instances. Concretely, the well-known…
Threatening Patch Attacks on Object Detection in Optical Remote Sensing Images
Xuxiang Sun, Gong Cheng, Lei Pei +2
Advanced Patch Attacks (PAs) on object detection in natural images have pointed out the great safety vulnerability in methods based on deep neural networks. However, little attenti…
Fewer is More: Efficient Object Detection in Large Aerial Images
Xingxing Xie, Gong Cheng, Qingyang Li +3
Current mainstream object detection methods for large aerial images usually divide large images into patches and then exhaustively detect the objects of interest on all patches, no…
DyRRen: A Dynamic Retriever-Reranker-Generator Model for Numerical Reasoning over Tabular and Textual Data
Xiao Li, Yin Zhu, Sichen Liu +3
Numerical reasoning over hybrid data containing tables and long texts has recently received research attention from the AI community. To generate an executable reasoning program co…
Knowledge Base Question Answering: A Semantic Parsing Perspective
Yu Gu, Vardaan Pahuja, Gong Cheng +1
Recent advances in deep learning have greatly propelled the research on semantic parsing. Improvement has since been made in many downstream tasks, including natural language inter…
Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding
Dongzhuoran Zhou, Baifan Zhou, Jieying Chen +3
Knowledge graphs (KG) are used in a wide range of applications. The automation of KG generation is very desired due to the data volume and variety in industries. One important appr…
Towards Large-Scale Small Object Detection: Survey and Benchmarks
Gong Cheng, Xiang Yuan, Xiwen Yao +4
With the rise of deep convolutional neural networks, object detection has achieved prominent advances in past years. However, such prosperity could not camouflage the unsatisfactor…
Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation
Chunbo Lang, Binfei Tu, Gong Cheng +1
Few-shot segmentation, which aims to segment unseen-class objects given only a handful of densely labeled samples, has received widespread attention from the community. Existing ap…
Learning What Not to Segment: A New Perspective on Few-Shot Segmentation
Chunbo Lang, Gong Cheng, Binfei Tu +1
Recently few-shot segmentation (FSS) has been extensively developed. Most previous works strive to achieve generalization through the meta-learning framework derived from classific…
AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension
Xiao Li, Gong Cheng, Ziheng Chen +2
Recent machine reading comprehension datasets such as ReClor and LogiQA require performing logical reasoning over text. Conventional neural models are insufficient for logical reas…
When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions
Zixian Huang, Ao Wu, Yulin Shen +2
Scenario-based question answering (SQA) requires retrieving and reading paragraphs from a large corpus to answer a question which is contextualized by a long scenario description.…
Oriented R-CNN for Object Detection
Xingxing Xie, Gong Cheng, Jiabao Wang +2
Current state-of-the-art two-stage detectors generate oriented proposals through time-consuming schemes. This diminishes the detectors' speed, thereby becoming the computational bo…
TSQA: Tabular Scenario Based Question Answering
Xiao Li, Yawei Sun, Gong Cheng
Scenario-based question answering (SQA) has attracted an increasing research interest. Compared with the well-studied machine reading comprehension (MRC), SQA is a more challenging…
Neural Entity Summarization with Joint Encoding and Weak Supervision
Junyou Li, Gong Cheng, Qingxia Liu +4
In a large-scale knowledge graph (KG), an entity is often described by a large number of triple-structured facts. Many applications require abridged versions of entity descriptions…
SPARQA: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Bases
Yawei Sun, Lingling Zhang, Gong Cheng +1
Semantic parsing transforms a natural language question into a formal query over a knowledge base. Many existing methods rely on syntactic parsing like dependencies. However, the a…
DeepLENS: Deep Learning for Entity Summarization
Qingxia Liu, Gong Cheng, Yuzhong Qu
Entity summarization has been a prominent task over knowledge graphs. While existing methods are mainly unsupervised, we present DeepLENS, a simple yet effective deep learning mode…
ESBM: An Entity Summarization BenchMark
Qingxia Liu, Gong Cheng, Kalpa Gunaratna +1
Entity summarization is the problem of computing an optimal compact summary for an entity by selecting a size-constrained subset of triples from RDF data. Entity summarization supp…
Relaxing Relationship Queries on Graph Data
Shuxin Li, Gong Cheng, Chengkai Li
In many domains we have witnessed the need to search a large entity-relation graph for direct and indirect relationships between a set of entities specified in a query. A search re…
GREASE: A Generative Model for Relevance Search over Knowledge Graphs
Tianshuo Zhou, Ziyang Li, Gong Cheng +2
Relevance search is to find top-ranked entities in a knowledge graph (KG) that are relevant to a query entity. Relevance is ambiguous, particularly over a schema-rich KG like DBped…
Entity Summarization: State of the Art and Future Challenges
Qingxia Liu, Gong Cheng, Kalpa Gunaratna +1
The increasing availability of semantic data has substantially enhanced Web applications. Semantic data such as RDF data is commonly represented as entity-property-value triples. T…
Towards More Usable Dataset Search: From Query Characterization to Snippet Generation
Jinchi Chen, Xiaxia Wang, Gong Cheng +2
Reusing published datasets on the Web is of great interest to researchers and developers. Their data needs may be met by submitting queries to a dataset search engine to retrieve r…
GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level
Zixian Huang, Yulin Shen, Xiao Li +5
Scenario-based question answering (SQA) has attracted increasing research attention. It typically requires retrieving and integrating knowledge from multiple sources, and applying…
A Framework for Evaluating Snippet Generation for Dataset Search
Xiaxia Wang, Jinchi Chen, Shuxin Li +4
Reusing existing datasets is of considerable significance to researchers and developers. Dataset search engines help a user find relevant datasets for reuse. They can present a sni…
Graph-based Ontology Summarization: A Survey
Seyedamin Pouriyeh, Mehdi Allahyari, Qingxia Liu +4
Ontologies have been widely used in numerous and varied applications, e.g., to support data modeling, information integration, and knowledge management. With the increasing size of…