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Found 5 papers, 1 papers with code
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction
On the one hand, retrieving good demonstrations is a non-trivial process in RE, which easily results in low relevance regarding entities and relations.
CMNEE: A Large-Scale Document-Level Event Extraction Dataset based on Open-Source Chinese Military News
To alleviate this problem, we propose CMNEE, a large-scale, document-level open-source Chinese Military News Event Extraction dataset.
Attention Guidance Mechanism for Handwritten Mathematical Expression Recognition
Handwritten mathematical expression recognition (HMER) is challenging in image-to-text tasks due to the complex layouts of mathematical expressions and suffers from problems including over-parsing and under-parsing.
Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction
The in-context learning (ICL) for relational triple extraction (RTE) has achieved promising performance, but still encounters two key challenges: (1) how to design effective prompts and (2) how to select proper demonstrations.
Revisiting Large Language Models as Zero-shot Relation Extractors
On the one hand, we analyze the drawbacks of existing RE prompts and attempt to incorporate recent prompt techniques such as chain-of-thought (CoT) to improve zero-shot RE.
