Tag: AI model training
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Annotator Training Boosts Competence in Social Influence AI
Discover how annotation improves annotator skills and enhances AI models in social influence recognition through expert and non-expert analysis.
Provenance-Based Gradient Guidance for Synthetic Data Learning
Enhance machine learning with provenance-based input gradient guidance to improve synthetic data training and reduce spurious correlations effectively.
Do Audio-Visual Large Language Models Truly See and Hear?
Explore how Audio-Visual Large Language Models integrate audio and visual inputs, revealing challenges in multimodal perception and training biases.
Fast, Accurate Probing of In-Training LLM Performance
Discover a new lightweight probing method to quickly and accurately evaluate in-training LLMs' downstream performance, boosting AI model development.
Scalable Pretraining of Large MoE Language Models on Aurora
Discover scalable pretraining of large Mixture of Experts language models using the Aurora supercomputer with high GPU efficiency and advanced optimization...