The space is dedicated to recording and summarizing scientific articles on text processing. It focuses on LLMs and their architectures, quantizations, tools, techniques, and models. It also includes articles on what is being produced in the field of classical machine learning in text processing.
Some topics and subjects that I am interested in and have set aside to read include:
- Semantic Similarity
- Security in LLMs and prompt injections + jailbreaks techniques;
- Interpretability and Explainability of LLMs;
- Decision-making in workflows and topic shifts;
- Context Learning and RAG.