PIVOT Explained — From Paper to Working Code in 10 Minutes
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You enabled sparse attention. Your model still chokes at 128K tokens. The indexer is why — and PIVOT fixes it without touching your weights. TL;DR Sparse attention's indexer scores all L tokens per query → still O(L²) PIVOT groups nearby queries (which select ~90% overlapping top-k tokens), runs one proxy scan per group → O(L²/g) Result: 4× indexer speedup , 1.6× end-to-end latency reduction on DeepSeek-V3.2 and GLM-5.1 Training-free: plug into existing DSA models at inference time Two modes:…
1Key Takeaways
- Your model still chokes at 128K tokens.
- The indexer is why — and PIVOT fixes it without touching your weights.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that your model still chokes at 128K tokens.
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