The paper proposes Multi-Head Recurrent Memory (MHM) with a select-then-update strategy to improve memory retention in long-context recurrent agents.
Infllm: Training-free long-context extrapolation for llms with an efficient context memory.Advances in neural information processing systems, 37:119638–119661
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
DashAttention introduces differentiable adaptive sparse hierarchical attention via α-entmax block selection, achieving full-attention accuracy at 75% sparsity with improved Pareto performance over NSA and InfLLMv2.
citing papers explorer
-
Multi-Head Recurrent Memory Agents
The paper proposes Multi-Head Recurrent Memory (MHM) with a select-then-update strategy to improve memory retention in long-context recurrent agents.
-
DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention
DashAttention introduces differentiable adaptive sparse hierarchical attention via α-entmax block selection, achieving full-attention accuracy at 75% sparsity with improved Pareto performance over NSA and InfLLMv2.