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[GH-ISSUE #118] Proposal: Symbolic Activation — 95% Compression & No Context Rot #108

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opened 2026-10-26 21:07:57 +00:00 by bsakaguchi · 0 comments
bsakaguchi commented 2026-10-26 21:07:57 +00:00
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Originally created by @gymaira1990-jpg on GitHub (May 28, 2026).
Original GitHub issue: https://github.com/deepseek-ai/DeepSeek-V2/issues/118

Hi @guosheng @deepseek-ai,

I'm GCat, and I've published research identifying Context Rot—a critical flaw in KV caching that degrades LLM performance in long conversations.

Key findings:

  • After 15+ turns / 32k tokens, effective info utilization drops below 40%
  • Root cause: Transformer + explicit KV cache, not long-context capability
  • Solution: Symbolic Activation Framework → 95% compression, zero context pollution

Paper: https://zenodo.org/records/20433184
Code: https://github.com/gymaira1990-jpg/catnest/tree/main/00-%E8%AE%BA%E6%96%87%E5%90%88%E9%9B%86

I would love to hear your thoughts on feasibility of integrating this into DeepSeek inference.

Thanks!
GCat

Originally created by @gymaira1990-jpg on GitHub (May 28, 2026). Original GitHub issue: https://github.com/deepseek-ai/DeepSeek-V2/issues/118 Hi @guosheng @deepseek-ai, I'm GCat, and I've published research identifying **Context Rot**—a critical flaw in KV caching that degrades LLM performance in long conversations. Key findings: - After 15+ turns / 32k tokens, effective info utilization drops below 40% - Root cause: Transformer + explicit KV cache, not long-context capability - Solution: **Symbolic Activation Framework** → 95% compression, zero context pollution Paper: https://zenodo.org/records/20433184 Code: https://github.com/gymaira1990-jpg/catnest/tree/main/00-%E8%AE%BA%E6%96%87%E5%90%88%E9%9B%86 I would love to hear your thoughts on feasibility of integrating this into DeepSeek inference. Thanks! GCat
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