Projective KV-Cache: Slashing LLM Memory Costs by 50%–75% Without Context Amnesia (Empirical Validation on GPT-2) The Executive Problem: Large Language Models (LLMs) processing long documents face an expensive bottleneck: the Key-Value (KV) Cache. Storing every token's attention memory in GPU VRAM creates immense hardw...
Andres Sebaatian Pirolo· Zenodo (CERN European Organi...· 0 citations
Projective KV-Cache: Slashing LLM Memory Costs by 50%–75% Without Context Amnesia (Empirical Validation on GPT-2) The Executive Problem: Large Language Models (LLMs) processing long documents face an expensive bottleneck: the Key-Value (KV) Cache. Storing every token's attention memory in GPU VRAM creates immense hardw...
Andres Sebaatian Pirolo· Zenodo (CERN European Organi...· 0 citations
Autonomous Spacecraft Detumbling Under Severe Tip-Off The Problem Small satellite missions in Low Earth Orbit (LEO) face critical survival risks during post-launch separation or emergency safe-modes. In these phases, violent multi-axis tumbling rates (exceeding 90°/s) blind high-precision optical sensors and saturate m...
Andres Sebaatian Pirolo· Zenodo (CERN European Organi...· 0 citations
Autonomous Spacecraft Detumbling Under Severe Tip-Off The Problem Small satellite missions in Low Earth Orbit (LEO) face critical survival risks during post-launch separation or emergency safe-modes. In these phases, violent multi-axis tumbling rates (exceeding 90°/s) blind high-precision optical sensors and saturate m...
Andres Sebaatian Pirolo· Zenodo (CERN European Organi...· 0 citations
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