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pro vyhledávání: '"Tanneru, Sree Harsha"'
As Large Language Models (LLMs) are increasingly being employed in real-world applications in critical domains such as healthcare, it is important to ensure that the Chain-of-Thought (CoT) reasoning generated by these models faithfully captures their
Externí odkaz:
http://arxiv.org/abs/2406.10625
Large Language Models (LLMs) are deployed as powerful tools for several natural language processing (NLP) applications. Recent works show that modern LLMs can generate self-explanations (SEs), which elicit their intermediate reasoning steps for expla
Externí odkaz:
http://arxiv.org/abs/2402.04614
Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit intermediate reasoning steps and key tokens that serve as proxy explan
Externí odkaz:
http://arxiv.org/abs/2311.03533
Autor:
Lin, Alexander, Paes, Lucas Monteiro, Tanneru, Sree Harsha, Srinivas, Suraj, Lakkaraju, Himabindu
Text-to-image models take a sentence (i.e., prompt) and generate images associated with this input prompt. These models have created award wining-art, videos, and even synthetic datasets. However, text-to-image (T2I) models can generate images that u
Externí odkaz:
http://arxiv.org/abs/2306.05500