Nov. 15, 2023, 7:03 p.m. | Arham Islam

MarkTechPost www.marktechpost.com

Large Language Models (LLMs) have shown remarkable capabilities in tasks like language understanding and reasoning, marking a paradigm shift in how we interact with AI systems. To augment the proficiency of LLMs, researchers generally employ the chain of thought prompting technique, which involves intermediate reasoning steps to guide the model’s response. Although this technique is […]


The post Can Language Models Reason Beyond Words? Exploring Implicit Reasoning in Multi-Layer Hidden States for Complex Tasks appeared first on MarkTechPost.

ai shorts ai systems applications artificial intelligence beyond capabilities chain of thought editors pick hidden intermediate language language model language models language understanding large language large language model large language models layer llms machine learning paradigm prompting reason reasoning researchers shift staff systems tasks tech news technology thought understanding words

More from www.marktechpost.com / MarkTechPost

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York