Tag: causal machine learning
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ECHO: Adaptive Critics for Enhanced Open-World RL Agents
Discover ECHO, a co-evolving critic framework improving feedback and training stability for open-world reinforcement learning agents.
League of LLMs: Benchmark-Free Evaluation for AI Models
Discover League of LLMs, a novel benchmark-free paradigm enabling mutual, transparent, and objective evaluation of large language models.
SmellNet: Large Dataset for AI Real-World Smell Detection
Explore SmellNet, a large-scale dataset powering AI to recognize real-world smells for healthcare, food safety, and environmental monitoring.
Optimizing Vision-Language Models for CT Enterography Analysis
Explore how representation geometry impacts vision-language modeling to improve CT enterography task performance and automated IBD assessment accuracy.
On-Policy Distillation of Large Language Models: Insights & Tips
Explore key mechanisms and strategies for effective on-policy distillation of large language models to boost training success and model performance.