HGA uses RoPE-aware chunk summaries for two-level hierarchical routing to approximate dense causal attention at 3% sparsity with 0.01-0.02 nats quality gap, as a drop-in replacement requiring no retraining.
Qwen3-30B-A3B-Instruct-2507-FP8 model card
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Hierarchical Global Attention (HGA)
HGA uses RoPE-aware chunk summaries for two-level hierarchical routing to approximate dense causal attention at 3% sparsity with 0.01-0.02 nats quality gap, as a drop-in replacement requiring no retraining.