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Found 7 papers, 2 papers with code
Position Paper: Agent AI Towards a Holistic Intelligence
Recent advancements in large foundation models have remarkably enhanced our understanding of sensory information in open-world environments.
An Interactive Agent Foundation Model
We propose an Interactive Agent Foundation Model that uses a novel multi-task agent training paradigm for training AI agents across a wide range of domains, datasets, and tasks.
Agent AI: Surveying the Horizons of Multimodal Interaction
To accelerate research on agent-based multimodal intelligence, we define "Agent AI" as a class of interactive systems that can perceive visual stimuli, language inputs, and other environmentally-grounded data, and can produce meaningful embodied actions.
MindAgent: Emergent Gaming Interaction
Large Language Models (LLMs) have the capacity of performing complex scheduling in a multi-agent system and can coordinate these agents into completing sophisticated tasks that require extensive collaboration.
Differentially Private Video Activity Recognition
In recent years, differential privacy has seen significant advancements in image classification; however, its application to video activity recognition remains under-explored.
Speech Representations and Phoneme Classification for Preserving the Endangered Language of Ladin
To address this problem in the context of Ladin, our paper presents the first analysis of speech representations and machine learning models for classifying 32 phonemes of Ladin.
Deep CNN Frame Interpolation with Lessons Learned from Natural Language Processing
A major area of growth within deep learning has been the study and implementation of convolutional neural networks.
