The development of artificial intelligence (ai), particularly large language models (LLMs), is focused on aligning these models with human preferences ...
A new one investigation addresses a critical problem in large multimodal language models (MLLMs): the phenomenon of object hallucination. Object ...
Aligning large language models (LLMs) to human expectations without human-annotated preference data is a major problem. In this paper, we ...
Aligning models with human preferences poses significant challenges in ai research, particularly in sequential and high-dimensional decision-making tasks. Traditional reinforcement ...
Contrastive learning typically relates pairs of related views among a series of unrelated negative views. Views can be generated (for ...
Recent advances in large visual language models (VLMs) have shown promise in addressing multimodal tasks by combining the reasoning capabilities ...
Contrastive pretraining using large, noisy text and image data sets has become popular for building overview representations. These models align ...
Diffusion models have proven to be very successful in producing high-quality photographs when given text suggestions. This paradigm for text-to-image ...
Information retrieval (IR) models have the ability to sort and classify documents based on user queries, facilitating efficient and effective ...
The challenge of matching human preferences to large pre-trained models has gained importance in the study as these models have ...
