When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
Evaluating large language models: A comprehensive survey
Large language models (LLMs) have demonstrated remarkable capabilities across a broad
spectrum of tasks. They have attracted significant attention and been deployed in numerous …
spectrum of tasks. They have attracted significant attention and been deployed in numerous …
A survey of large language models
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
Graph of thoughts: Solving elaborate problems with large language models
Abstract We introduce Graph of Thoughts (GoT): a framework that advances prompting
capabilities in large language models (LLMs) beyond those offered by paradigms such as …
capabilities in large language models (LLMs) beyond those offered by paradigms such as …
Program of thoughts prompting: Disentangling computation from reasoning for numerical reasoning tasks
Recently, there has been significant progress in teaching language models to perform step-
by-step reasoning to solve complex numerical reasoning tasks. Chain-of-thoughts prompting …
by-step reasoning to solve complex numerical reasoning tasks. Chain-of-thoughts prompting …
Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct
Large language models (LLMs), such as GPT-4, have shown remarkable performance in
natural language processing (NLP) tasks, including challenging mathematical reasoning …
natural language processing (NLP) tasks, including challenging mathematical reasoning …
Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms
The task of empowering large language models (LLMs) to accurately express their
confidence, referred to as confidence elicitation, is essential in ensuring reliable and …
confidence, referred to as confidence elicitation, is essential in ensuring reliable and …
Promptbreeder: Self-referential self-improvement via prompt evolution
Popular prompt strategies like Chain-of-Thought Prompting can dramatically improve the
reasoning abilities of Large Language Models (LLMs) in various domains. However, such …
reasoning abilities of Large Language Models (LLMs) in various domains. However, such …
Compositional chain-of-thought prompting for large multimodal models
The combination of strong visual backbones and Large Language Model (LLM) reasoning
has led to Large Multimodal Models (LMMs) becoming the current standard for a wide range …
has led to Large Multimodal Models (LMMs) becoming the current standard for a wide range …
Reasoning on graphs: Faithful and interpretable large language model reasoning
Large language models (LLMs) have demonstrated impressive reasoning abilities in
complex tasks. However, they lack up-to-date knowledge and experience hallucinations …
complex tasks. However, they lack up-to-date knowledge and experience hallucinations …