Multi-Turn Agentic Context Decay & State Pollution: Benchmarking 18,432-D Poincaré Memory vs Gemini 3.5 & Gemma-4
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This is a submission for the Kaggle Benchmarking Challenge What I Benchmarked In continuous multi-agent engineering workflows, AI swarms reason over long execution sessions—executing dozens of tool calls, inspecting vast codebases, and mutating shared memory states. However, existing LLM agent fram…
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- 2026-10-09 18:32 · DEV Community — Machine Learning
Multi-Turn Agentic Context Decay & State Pollution: Benchmarking 18,432-D Poincaré Memory vs Gemini 3.5 & Gemma-4