******Retrieval/RAG privacy & robustness (PRISM, SPLADE, TurboQuant, Salomi)******
Key Questions
What is PRISM in RAG contexts?
PRISM achieves O(1) retrieval for privacy-preserving RAG, enhancing efficiency and robustness. It addresses privacy amid agentic systems.
How does Salomi advance quantization?
Salomi enables 1bpp extreme low-bit transformer quantization, balancing compression and performance. It supports efficient retrieval in LLMs.
What gains does TurboQuant provide?
TurboQuant offers 6x/8x speedups in LLM quantization, with TurboAngle ensuring lossless compression. These improve RAG robustness.
What RAG poisoning vulnerability did DeepMind identify?
DeepMind shows 80% success in RAG poisoning attacks, compromising retrieval integrity. This highlights privacy and robustness risks.
What is TriAttention for long reasoning?
TriAttention uses trigonometric KV compression for efficient long-context reasoning. It boosts RAG performance under token limits.
Swift-SVD low-rank compression; Salomi 1bpp; PRISM O(1); TurboQuant 6x/8x; TurboAngle lossless; DeepMind RAG poison 80%; TriAttention trig KV for long reasoning. Efficiency/privacy amid agents.