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Researchers from the Chinese Academy of Science, including Q Fang, S Guo, Y Zhou, and Z Ma, have introduced LLaMA-Omni, a seamless speech interaction model using large language models. Another development in the field is LLaFS, a method for few-shot segmentation in computer vision, leveraging large language models. Additionally, GLaMM, a new AI model, can understand both text and images, enabling detailed conversations and object identification in pictures.
#GPTs and Hallucination Why do large language models #hallucinate? https://t.co/XVZyTPl1IZ GPTs based on #LLMs perform well on prompts that are more popular and have reached a general consensus yet struggle on controversial topics or topics with limited data.
Graphical models struggle to explain patterns in text & images 😭 LLM can do this but hallucinates. 👿 It’s time to combine their strengths! We define models with natural language parameters! Unlocking opportunities in science, business, ML, etc https://t.co/LQ9rtCTxb2
GLaMM: Pixel Grounding Large Multimodal Model TLDR: GLaMM is a new AI model that can understand both text and images to have detailed conversations while pointing out objects in pictures. ✨ Interactive paper: https://t.co/pMv5NgRSWo
