Fine-tuning visual models has been widely shown promising performance on many
downstream visual tasks. With the surprising development of pre-trained visual foundation …

Large Language Models (LLMs) have drawn a lot of attention due to their strong
performance on a wide range of natural language tasks, since the release of ChatGPT in …

Despite significant strides in multimodal tasks, Multimodal Large Language Models (MLLMs)
are plagued by the critical issue of hallucination. The reliable detection of such …

We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to
applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a …

AI progress is creating a growing range of risks and opportunities, but it is often unclear how
they should be navigated. In many cases, the barriers and uncertainties faced are at least …

Recently, Foundation Models (FMs), with their extensive knowledge bases and complex
architectures, have offered unique opportunities within the realm of recommender systems …

The development of artificial intelligence systems is transitioning from creating static, task-
specific models to dynamic, agent-based systems capable of performing well in a wide …

Autonomous driving based on foundation models has recently garnered widespread
attention. However, the risk of hallucinations inherent in foundation models could …

Hallucination is a significant barrier to the utilization of large-scale language models or
multimodal models. In this study, we collected 654 computer science papers with" …

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