Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

We envision" AI scientists" as systems capable of skeptical learning and reasoning that
empower biomedical research through collaborative agents that integrate AI models and …

Language agents have achieved considerable performance on various complex tasks.
Despite the incessant exploration in this field, existing language agent systems still struggle …

Large language models (LLMs) have exhibited great potential in autonomously completing
tasks across real-world applications. Despite this, these LLM agents introduce unexpected …

In-context learning (ICL, also known as few-shot prompting) has been the standard method
of adapting LLMs to downstream tasks, by learning from a few input-output examples …

Intelligent agents powered by large language models (LLMs) have demonstrated substantial
promise in autonomously conducting experiments and facilitating scientific discoveries …

Foundation model-enabled generative artificial intelligence facilitates the development and
implementation of agents, which can leverage distinguished reasoning and language …

Large Language Models (LLMs) have demonstrated great potential in complex reasoning
tasks, yet they fall short when tackling more sophisticated challenges, especially when …

The field of natural language processing (NLP) has witnessed significant progress in recent
years, with a notable focus on improving large language models'(LLM) performance through …

Space-air-ground integrated networks (SAGINs) enable worldwide network coverage
beyond geographical limitations for users to access ubiquitous intelligence services.{\color …