Large language models for generative information extraction: A survey
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
Combating misinformation in the age of llms: Opportunities and challenges
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …
and public trust. The emergence of large language models (LLMs) has great potential to …
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 …
Towards reasoning in large language models: A survey
Reasoning is a fundamental aspect of human intelligence that plays a crucial role in
activities such as problem solving, decision making, and critical thinking. In recent years …
activities such as problem solving, decision making, and critical thinking. In recent years …
A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …
natural language processing (NLP), fueling a paradigm shift in information acquisition …
Promptbench: Towards evaluating the robustness of large language models on adversarial prompts
The increasing reliance on Large Language Models (LLMs) across academia and industry
necessitates a comprehensive understanding of their robustness to prompts. In response to …
necessitates a comprehensive understanding of their robustness to prompts. In response to …
Editing large language models: Problems, methods, and opportunities
Despite the ability to train capable LLMs, the methodology for maintaining their relevancy
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
and rectifying errors remains elusive. To this end, the past few years have witnessed a surge …
Towards open-world recommendation with knowledge augmentation from large language models
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …
nature of training and deploying separately within a specific closed domain limits its access …
Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities
This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …