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Found 4 papers, 3 papers with code
Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction
Additionally, our method is orthogonal to previous multimodal fusions, and using it on prior SOTA fusions further improves 5. 47% F1.
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction
However, existing works often struggle to obtain class prototypes with accurate relational semantics: 1) To build prototype for a target relation type, they aggregate the representations of all entity pairs holding that relation, while these entity pairs may also hold other relations, thus disturbing the prototype.
A Semantic Invariant Robust Watermark for Large Language Models
In this work, we propose a semantic invariant watermarking method for LLMs that provides both attack robustness and security robustness.
Gradient Imitation Reinforcement Learning for General Low-Resource Information Extraction
Low-Resource Information Extraction (LRIE) strives to use unsupervised data, reducing the required resources and human annotation.
