Large Language Models (LMMs) are developing significantly and proving to be capable of handling more complicated jobs that call for a blend of different integrated skills. Among these jobs include GUI navigation, converting images to code, and comprehending films. A number of benchmarks, including MME, MMBench, SEEDBench, MMMU, and MM-Vet, have been established in order… →

Machine learning models integrating text and images have become pivotal in advancing capabilities across various applications. These multimodal models are designed to process and understand combined textual and visual data, which enhances tasks such as answering questions about images, generating descriptions, or creating content based on multiple images. They are crucial for improving document comprehension… →

Multimodal models are designed to make human-computer interaction more intuitive and natural, enabling machines to understand and respond to human inputs in ways that closely mirror human communication. This progress is crucial for advancing applications across various industries, including healthcare, education, and entertainment. One of the main challenges in AI development is ensuring these powerful… →

Large-scale multimodal foundation models have achieved notable success in understanding complex visual patterns and natural language, generating interest in their application to medical vision-language tasks. Progress has been made by creating medical datasets with image-text pairs and fine-tuning general domain models on these datasets. However, these datasets have limitations. They lack multi-granular annotations that link… →

The ability to convert natural language questions into structured query language (SQL), known as text-to-SQL, helps non-experts easily interact with databases using natural language. This makes data access and analysis more accessible to everyone. Recent studies have highlighted significant achievements in powerful closed-source large language models (LLMs) like GPT-4, which use advanced prompting techniques. However,… →

As LLMs have become increasingly capable of performing various tasks through few-shot learning and instruction following, their inconsistent output formats have hindered their reliability and usability in industrial contexts. This inconsistency complicates the extraction and evaluation of generated content, particularly when structured generation methods, such as JSON and XML, are employed. The authors investigate whether… →

Over 300,000 photos in earlier massive datasets like COCO have over 3 million annotations. Models may now be trained on datasets with a 1000x increase in scale, such as FLD-5B, which contains over 126 million photos annotated with five billion+ words. Annotation speed can be increased by a factor of 100 with synthetic annotation pipelines,… →