Dynamic Heads
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Positional versus Symbolic Attention Heads: Learning Dynamics, RoPE Geometry, and Length Generalization
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From Rigid to Dynamic: Entropy-Guided Adaptive Inference for Long-Context LLMs
arXiv:2606.09508v1 Announce Type: new Abstract: Existing sparse attention and KV cache compression methods for long-context LLM inference typically apply fixed sparsity patterns or uniform budgets across all attention heads, overlooking the substantial variation in attention behavior among heads and contexts. We observe two distinct entropy patterns among attention heads: Rigid Heads, whose entropy stays near zero across input segments, and Dynamic Heads, whose entropy fluctuates...
Adaptive Head Budgeting for Efficient Multi-Head Attention
arXiv:2604.22583v2 Announce Type: replace Abstract: Multi-head attention enables Transformers to capture diverse representations, but all attention heads are typically activated for every input, regardless of task complexity. For coarse-grained tasks such as text classification, where relevant information is often global, this fixed allocation can introduce unnecessary computation. We propose BudgetFormer, a Transformer architecture that dynamically allocates attention heads on a per-input...
Adaptive Head Budgeting for Efficient Multi-Head Attention
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Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting
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Representation over Routing: Diagnosing Temporal Routing Pathologies in Multi-Timescale PPO
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Echo: A Joint-Embedding Predictive Architecture for Speaker Diarization and Speech Recognition in a Shared Latent Space
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Estimating Central, Peripheral, and Temporal Visual Contributions to Human Decision Making in Atari Games
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Mamba-Enhanced Implicit Motion Learning for Audio-Driven Portrait Animation
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Mamba-Enhanced Implicit Motion Learning for Audio-Driven Portrait Animation
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