History, development, and principles of large language models: an introductory survey
Abstract Language models serve as a cornerstone in natural language processing, utilizing
mathematical methods to generalize language laws and knowledge for prediction and …
mathematical methods to generalize language laws and knowledge for prediction and …
Llms4ol 2024 overview: The 1st large language models for ontology learning challenge
This paper outlines the LLMs4OL 2024, the first edition of the Large Language Models for
Ontology Learning Challenge. LLMs4OL is a community development initiative collocated …
Ontology Learning Challenge. LLMs4OL is a community development initiative collocated …
Assessment of fine-tuned large language models for real-world chemistry and material science applications
The current generation of large language models (LLMs) has limited chemical knowledge.
Recently, it has been shown that these LLMs can learn and predict chemical properties …
Recently, it has been shown that these LLMs can learn and predict chemical properties …
Aligning llms to be robust against prompt injection
Large language models (LLMs) are becoming increasingly prevalent in modern software
systems, interfacing between the user and the internet to assist with tasks that require …
systems, interfacing between the user and the internet to assist with tasks that require …
xgen-mm-vid (blip-3-video): You only need 32 tokens to represent a video even in vlms
We present xGen-MM-Vid (BLIP-3-Video): a multimodal language model for videos,
particularly designed to efficiently capture temporal information over multiple frames. BLIP-3 …
particularly designed to efficiently capture temporal information over multiple frames. BLIP-3 …
Re-task: Revisiting llm tasks from capability, skill, and knowledge perspectives
Z Wang, S Zhao, Y Wang, H Huang, S **e… - arxiv preprint arxiv …, 2024 - arxiv.org
The Chain-of-Thought (CoT) paradigm has become a pivotal method for solving complex
problems. However, its application to intricate, domain-specific tasks remains challenging …
problems. However, its application to intricate, domain-specific tasks remains challenging …
A scalable communication protocol for networks of large language models
Communication is a prerequisite for collaboration. When scaling networks of AI-powered
agents, communication must be versatile, efficient, and portable. These requisites, which we …
agents, communication must be versatile, efficient, and portable. These requisites, which we …
Critic-cot: Boosting the reasoning abilities of large language model via chain-of-thoughts critic
Self-critic has become a crucial mechanism for enhancing the reasoning performance of
LLMs. However, current approaches mainly involve basic prompts for intuitive instance-level …
LLMs. However, current approaches mainly involve basic prompts for intuitive instance-level …
Memory layers at scale
Memory layers use a trainable key-value lookup mechanism to add extra parameters to a
model without increasing FLOPs. Conceptually, sparsely activated memory layers …
model without increasing FLOPs. Conceptually, sparsely activated memory layers …
Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities
The advancement of Large Language Models (LLMs) for domain applications in fields such
as materials science and engineering depends on the development of fine-tuning strategies …
as materials science and engineering depends on the development of fine-tuning strategies …