6 papers
FSE: Continual Learning for Named Entity Recognition by Fast-Slow Experts
Yunan Zhang, Yang Fan, Heng Li +2
Continual Learning for Named Entity Recognition (CLNER) enable models to incrementally learn new entity types without forgetting previously acquired ones. However, existing methods…
WaterSearch: Exploring Seed Pooling for Improving the Quality-Detectability Trade-off in LLM Watermarking
Yukang Lin, Jiahao Shao, Shuoran Jiang +5
Watermarking acts as a critical safeguard in text generated by Large Language Models (LLMs). By embedding identifiable signals into model outputs, watermarking enables reliable att…
D2Dewarp: Dual Dimensions Geometric Representation Learning Based Document Image Dewarping
Heng Li, Xiangping Wu, Qingcai Chen
Document image dewarping remains a challenging task in the deep learning era. While existing methods have improved by leveraging text line awareness, they typically focus only on a…
GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay
Yunan Zhang, Shuoran Jiang, Mengchen Zhao +4
The continual learning capability of large language models (LLMs) is crucial for advancing artificial general intelligence. However, continual fine-tuning LLMs across various domai…
Document Image Rectification Bases on Self-Adaptive Multitask Fusion
Heng Li, Xiangping Wu, Qingcai Chen
Deformed document image rectification is essential for real-world document understanding tasks, such as layout analysis and text recognition. However, current multi-task methods --…
CrossFormer: Cross-Segment Semantic Fusion for Document Segmentation
Tongke Ni, Yang Fan, Junru Zhou +2
Text semantic segmentation involves partitioning a document into multiple paragraphs with continuous semantics based on the subject matter, contextual information, and document str…