LG AI Research's Data Intelligence Lab presented two papers at AAMAS 2024 on multi-agent reinforcement learning for real-world applications: one on naphtha cracking center scheduling optimization and…
Google released new Gemma2 models in 9b and 27b sizes, described as overtrained on tokens and distilled from larger Gemini models, with alternating global/local attention layers.
XLSCOUT Unveils ParaEmbed 2.0: a Powerful Embedding Model Tailored for Patents and IP with Expert Support from Hugging Face
XLSCOUT released ParaEmbed 2.0, a proprietary embedding model for patent analysis, developed with Hugging Face's Expert Support Program, achieving a 23% accuracy improvement over ParaEmbed 1.0.
This blog post by Hugging Face demonstrates how to fine-tune Microsoft's Florence-2 vision-language model on the DocVQA dataset, showing that after fine-tuning the Levenshtein similarity score…
[AAMAS 2024] Multi-Agent Reinforcement Learning for Real-World Application (Part 2)
The blog post discusses two papers from AAMAS 2024 on improvements in asynchronous multi-agent reinforcement learning and offline multi-agent reinforcement learning.