4 citations · 6 across the 8 of their papers we have counts for
8 papers
Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganography
Ruiyi Yan, Shiao Meng, Yugo Murawaki
Linguistic steganography based on language models typically assumes that steganographic texts are transmitted without alteration, making them fragile to even minor modifications. W…
GenCNER: A Generative Framework for Continual Named Entity Recognition
Yawen Yang, Fukun Ma, Shiao Meng +2
Traditional named entity recognition (NER) aims to identify text mentions into pre-defined entity types. Continual Named Entity Recognition (CNER) is introduced since entity catego…
GapDNER: A Gap-Aware Grid Tagging Model for Discontinuous Named Entity Recognition
Yawen Yang, Fukun Ma, Shiao Meng +2
In biomedical fields, one named entity may consist of a series of non-adjacent tokens and overlap with other entities. Previous methods recognize discontinuous entities by connecti…
On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations
Shiao Meng, Xuming Hu, Aiwei Liu +4
Driven by the demand for cross-sentence and large-scale relation extraction, document-level relation extraction (DocRE) has attracted increasing research interest. Despite the cont…
Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction
Xuming Hu, Junzhe Chen, Aiwei Liu +3
How can we better extract entities and relations from text? Using multimodal extraction with images and text obtains more signals for entities and relations, and aligns them throug…
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction
Shiao Meng, Xuming Hu, Aiwei Liu +4
How to identify semantic relations among entities in a document when only a few labeled documents are available? Few-shot document-level relation extraction (FSDLRE) is crucial for…
A Semantic Invariant Robust Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu +2
Watermark algorithms for large language models (LLMs) have achieved extremely high accuracy in detecting text generated by LLMs. Such algorithms typically involve adding extra wate…
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction
Xuming Hu, Shiao Meng, Chenwei Zhang +4
Information Extraction (IE) aims to extract structured information from heterogeneous sources. IE from natural language texts include sub-tasks such as Named Entity Recognition (NE…