6 results for "multimodal models"
Most efficient way of running Gemma 4 E4B with multimodal capabilities on a laptop?
The gemma 4 E4B and E2B models have built-in multimodal capabilities. However, as far as I am aware, llama.cpp does not have proper support for vision and audio inputs (specially audio) for these mode…
FAIR_XAI: Improving Multimodal Foundation Model Fairness via Explainability for Wellbeing Assessment
In recent years, the integration of multimodal machine learning in wellbeing assessment has offered transformative potential for monitoring mental health. However, with the rapid advancement of Vision…
MIMIC: A Generative Multimodal Foundation Model for Biomolecules
Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained within one modality or f…
NVIDIA Launches Nemotron 3 Nano Omni Model, Unifying Vision, Audio and Language for up to 9x More Efficient AI Agents
AI agent systems today juggle separate models for vision, speech and language — losing time and context as they pass data from one model to the other. Unveiled today, NVIDIA Nemotron 3 Nano Omni is an…
StoryTR: Narrative-Centric Video Temporal Retrieval with Theory of Mind Reasoning
Current video moment retrieval excels at action-centric tasks but struggles with narrative content. Models can see \textit{what is happening} but fail to reason \textit{why it matters}. This semantic …
Grounding Before Generalizing: How AI Differs from Humans in Causal Transfer
Extracting abstract causal structures and applying them to novel situations is a hallmark of human intelligence. While Large Language Models (LLMs) and Vision Language Models (VLMs) have shown strong …