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[HTML][HTML] Ptr: Prompt tuning with rules for text classification
Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-
trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved …
trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved …
Document-level relation extraction with adaptive focal loss and knowledge distillation
Multimodal relation extraction with efficient graph alignment
Relation extraction (RE) is a fundamental process in constructing knowledge graphs.
However, previous methods on relation extraction suffer sharp performance decline in short …
However, previous methods on relation extraction suffer sharp performance decline in short …
Virtual prompt pre-training for prototype-based few-shot relation extraction
Prompt tuning with pre-trained language models (PLM) has exhibited outstanding
performance by reducing the gap between pre-training tasks and various downstream …
performance by reducing the gap between pre-training tasks and various downstream …
An improved baseline for sentence-level relation extraction
Sentence-level relation extraction (RE) aims at identifying the relationship between two
entities in a sentence. Many efforts have been devoted to this problem, while the best …
entities in a sentence. Many efforts have been devoted to this problem, while the best …
ERICA: Improving entity and relation understanding for pre-trained language models via contrastive learning
Pre-trained Language Models (PLMs) have shown superior performance on various
downstream Natural Language Processing (NLP) tasks. However, conventional pre-training …
downstream Natural Language Processing (NLP) tasks. However, conventional pre-training …
Exploring task difficulty for few-shot relation extraction
Few-shot relation extraction (FSRE) focuses on recognizing novel relations by learning with
merely a handful of annotated instances. Meta-learning has been widely adopted for such a …
merely a handful of annotated instances. Meta-learning has been widely adopted for such a …
Semantic relation extraction: a review of approaches, datasets, and evaluation methods with looking at the methods and datasets in the Persian language
A large volume of unstructured data, especially text data, is generated and exchanged daily.
Consequently, the importance of extracting patterns and discovering knowledge from textual …
Consequently, the importance of extracting patterns and discovering knowledge from textual …
A novel pipelined end-to-end relation extraction framework with entity mentions and contextual semantic representation
The mainstream method of end-to-end relation extraction is to jointly extract entities and
relations by sharing span representation, which, however, may cause feature conflict. The …
relations by sharing span representation, which, however, may cause feature conflict. The …