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Found 8 papers, 5 papers with code
MMEKG: Multi-modal Event Knowledge Graph towards Universal Representation across Modalities
Events are fundamental building blocks of real-world happenings.
SciAgent: Tool-augmented Language Models for Scientific Reasoning
To make this task more practical and solvable for LLMs, we introduce a new task setting named tool-augmented scientific reasoning.
Learning To Teach Large Language Models Logical Reasoning
Large language models (LLMs) have gained enormous attention from both academia and industry, due to their exceptional ability in language generation and extremely powerful generalization.
Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution
Although achieving great success, Large Language Models (LLMs) usually suffer from unreliable hallucinations.
Few-shot Event Detection: An Empirical Study and a Unified View
Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e. g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress. This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline.
Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!
Large Language Models (LLMs) have made remarkable strides in various tasks.
Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction
We have conducted extensive experiments on three benchmarks, including both sentence- and document-level EAE.
Information Extraction in Low-Resource Scenarios: Survey and Perspective
Information Extraction (IE) seeks to derive structured information from unstructured texts, often facing challenges in low-resource scenarios due to data scarcity and unseen classes.
