报错解决-git报错

算法-哈希表

算法-数组

报错解决记录-算法篇

Doccano工具安装 + 使用

Learning "O" Helps for Learning More: Handling the Unlabeled Entity Problem for Class-incremental NER

GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer

Hero-Gang Neural Model For Named Entity Recognition

DABERT: Dual Attention Enhanced BERT for Semantic Matching

Nested Named Entity Recognition with Span-level Graphs

Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction

论文阅读：Enrel

Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents

代码阅读《Text-to-Table: A New Way of Information Extraction

LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding

BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents

Automated pipeline for superalloy data by text mining

Graph Convolution for Multimodal Information Extraction from Visually Rich Documents

Automated knowledge extraction from polymer literature using natural language processing

Masked Autoencoders Are Scalable Vision Learners

When Counting Meets HMER: Counting-Aware Network for Handwritten Mathematical Expression Recognition

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers