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Found 19 papers, 9 papers with code
Reasoning on Efficient Knowledge Paths:Knowledge Graph Guides Large Language Model for Domain Question Answering
Especially for the question that require a multi-hop reasoning path, frequent calls to LLM will consume a lot of computing power.
Cycle Invariant Positional Encoding for Graph Representation Learning
To efficiently encode the space of all cycles, we start with a cycle basis (i. e., a minimal set of cycles generating the cycle space) which we compute via the kernel of the 1-dimensional Hodge Laplacian of the input graph.
Recognition-Guided Diffusion Model for Scene Text Image Super-Resolution
Scene Text Image Super-Resolution (STISR) aims to enhance the resolution and legibility of text within low-resolution (LR) images, consequently elevating recognition accuracy in Scene Text Recognition (STR).
Efficiently Counting Substructures by Subgraph GNNs without Running GNN on Subgraphs
Among these works, a popular way is to use subgraph GNNs, which decompose the input graph into a collection of subgraphs and enhance the representation of the graph by applying GNN to individual subgraphs.
Improving Table Structure Recognition with Visual-Alignment Sequential Coordinate Modeling
The ablation study also validates that the proposed coordinate sequence decoder and the visual-alignment loss are the keys to the success of our method.
CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition
In this paper, we propose CoMER, a model that adopts the coverage information in the transformer decoder.
Neural Approximation of Graph Topological Features
Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods.
Cycle Representation Learning for Inductive Relation Prediction
In this paper, we consider rules as cycles and show that the space of cycles has a unique structure based on the mathematics of algebraic topology.
Graph Representation Learning
Inductive Relation Prediction
+1
A Topological View of Rule Learning in Knowledge Graphs
We propose to collect cycle bases that span the space of cycles.
Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer
Encoder-decoder models have made great progress on handwritten mathematical expression recognition recently.
MathBERT: A Pre-Trained Model for Mathematical Formula Understanding
Large-scale pre-trained models like BERT, have obtained a great success in various Natural Language Processing (NLP) tasks, while it is still a challenge to adapt them to the math-related tasks.
Automatic Description Construction for Math Expression via Topic Relation Graph
In the Selector, a Topic Relation Graph (TRG) is proposed to obtain the relevant documents which contain the comprehensive information of math expressions.
Community-based Cyberreading for Information Understanding
Although the content in scientific publications is increasingly challenging, it is necessary to investigate another important problem, that of scientific information understanding.
Link Prediction with Persistent Homology: An Interactive View
Link prediction is an important learning task for graph-structured data.
ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition
Despite the recent advances in optical character recognition (OCR), mathematical expressions still face a great challenge to recognize due to their two-dimensional graphical layout.
Optical Character Recognition
Optical Character Recognition (OCR)
Automatic Generation of Headlines for Online Math Questions
Compared to conventional summarization tasks, this task has two extra and essential constraints: 1) Detailed math questions consist of text and math equations which require a unified framework to jointly model textual and mathematical information; 2) Unlike text, math equations contain semantic and structural features, and both of them should be captured together.
Cross-language Citation Recommendation via Hierarchical Representation Learning on Heterogeneous Graph
While the volume of scholarly publications has increased at a frenetic pace, accessing and consuming the useful candidate papers, in very large digital libraries, is becoming an essential and challenging task for scholars.
Combining Pyramid Pooling and Attention Mechanism for Pelvic MR Image Semantic Segmentaion
One of the time-consuming routine work for a radiologist is to discern anatomical structures from tomographic images.
Using Deep Learning Method for Classification: A Proposed Algorithm for the ISIC 2017 Skin Lesion Classification Challenge
The models are built on the source images are using the Caffe [4] framework.
