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Found 5 papers, 1 papers with code
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models
When LLMs perform zero-shot inference, they typically use a prompt with a task specification, and generate a completion.
Exploring Group and Symmetry Principles in Large Language Models
Large Language Models (LLMs) have demonstrated impressive performance across a wide range of applications; however, assessing their reasoning capabilities remains a significant challenge.
DiversiGATE: A Comprehensive Framework for Reliable Large Language Models
In this paper, we introduce DiversiGATE, a unified framework that consolidates diverse methodologies for LLM verification.
Are uGLAD? Time will tell!
Segmentation of multivariate time series data is a technique for identifying meaningful patterns or changes in the time series that can signal a shift in the system's behavior.
MathPrompter: Mathematical Reasoning using Large Language Models
Large Language Models (LLMs) have limited performance when solving arithmetic reasoning tasks and often provide incorrect answers.
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