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Demonstration Augmentation for Zero-shot In-context Learning
Annual Meeting of the Association for Computational LinguisticsLarge Language Models (LLMs) have demonstrated an impressive capability known as In-context Learning (ICL), which enables them to acquire knowledge from textual demonstrations without the need for parameter updates. However, many studies have highlighted
Yi Su +5 more
semanticscholar +1 more source
Parrots misbehaving: LLM evidence from zero-probability linguistic tasks
The dominant theoretical model for large language models (LLMs) holds that they function as “stochastic parrots”: statistical systems that predict token sequences without genuine understanding. This claim, though widely accepted, has not been empirically validated beyond the training phase.openaire +1 more source
Zero-Shot Strategies for Length-Controllable Summarization
North American Chapter of the Association for Computational LinguisticsLarge language models (LLMs) struggle with precise length control, particularly in zero-shot settings. We conduct a comprehensive study evaluating LLMs' length control capabilities across multiple measures and propose practical methods to improve ...
Fabian Retkowski, Alexander Waibel
semanticscholar +1 more source
Engineered platforms for topological superconductivity and Majorana zero modes
Nature Reviews Materials, 2021Karsten Flensberg +2 more
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Integrated solar-driven PV cooling and seawater desalination with zero liquid discharge
Joule, 2021Wenbin Wang, Sara Aleid, Chenlin Zhang
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Compositionally complex doping for zero-strain zero-cobalt layered cathodes
Nature, 2022Chunyang Wang +2 more
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Zero Touch Management: A Survey of Network Automation Solutions for 5G and 6G Networks
IEEE Communications Surveys and Tutorials, 2022Estefanía Coronado +2 more
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Zero-Dimensional Carbon Nanomaterials for Fluorescent Sensing and Imaging
Chemical Reviews, 2023Zheng Yang, Meng-Yao She, Jiao Chen
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Recent progress of zero-dimensional luminescent metal halides
Chemical Society Reviews, 2021Zhiguo Xia
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