Search Results for author:
Found 6 papers, 2 papers with code
TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale
To overcome this, we introduce TriSum, a framework for distilling LLMs' text summarization abilities into a compact, local model.
GenRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Models
The field of relation extraction (RE) is experiencing a notable shift towards generative relation extraction (GRE), leveraging the capabilities of large language models (LLMs).
Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations
In this paper, we propose a novel method called GODE, which takes into account the two-level structure of individual molecules.
Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
The mission of open knowledge graph (KG) completion is to draw new findings from known facts.
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
This is because personalized predictions require personalized knowledge graphs (KGs), which are difficult to generate from patient EHR data.
OACAL: Finding Module-consistent Specifications to Secure Systems from Weakened User Obligations
To improve the security with the awareness of unexpected user behaviors, a system can be redesigned to a more robust one by changing the order of actions in its specification.
