Google’s new neural-net LLM architecture separates memory components to control exploding costs of capacity and compute
Titans architecture complements attention layers with neural memory modules that select bits of information worth saving in the long term.
InfoWorld2d
The journey towards a knowledge graph for generative AI
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper ...
From Generalist To Specialist: The Role Of SFT In LLM Evolution
While supervised fine-tuning is allowing LLMs to succeed in narrow contexts, it requires high-quality, domain-specific ...
BioSpace23d
Ractigen Therapeutics Announces First Patient Dosed in Phase I Clinical Trial for RAG-17 in SOD1-ALS
“The first patient dosed in the RAG-17 trial marks a pivotal milestone in our mission to combat ALS, one of the most devastating neurodegenerative diseases,” said Dr. Long-Cheng Li, Founder and CEO of ...
labs.sogeti24d
Building advanced RAG systems: Part 1
Other document elements like tables, diagrams and graphs often become an incoherent jumble of symbols and text which is unusable by the LLM. The downstream effect is that RAG systems perform well ...
IEEE24d
Hybrid RAG-Empowered Multi-Modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-Based Contract Approach
To this end, this paper proposes a hybrid Retrieval-Augmented Generation (RAG)-empowered medical MLLM framework for healthcare data management. The proposed framework enables secure data training by ...
marktechpost24d
Meet OREO (Offline REasoning Optimization): An Offline Reinforcement Learning Method for Enhancing LLM Multi-Step Reasoning
These obstacles highlight the need for more targeted and efficient solutions to enhance LLM reasoning capabilities. OREO (Offline REasoning Optimization) is an offline RL approach specifically ...
GitHub26d
llm-ui
Add a description, image, and links to the llm-ui topic page so that developers can more easily learn about it.