Prefill-Free Cross-Family KV Cache Transfer for Heterogeneous Multi-Agent LLMs
How to Hand Off KV Caches As-Is Between Different LLMs: HeteroFold TL;DR: HeteroFold, a method that reuses the KV cache between models with different tokenizers and…
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Adapting Tree-Structured Speculative Decoding to DeepSeek-V4 for Efficient Inference
Branching on Compressed Memory: Adding Tree Reasoning to DeepSeek-V4 TL;DR Adding tree-structured speculative decoding to DeepSeek-V4-Flash yields longer acceptance…
Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs
Flash-dLLM: I/O-First Diffusion LLM Acceleration, Unlocking 210.6 tokens/s with Fused Cache and Self-Verification One-Line Summary (TL;DR) Diffusion LLMs (dLLMs) support…
H-Spec: Parallel Speculative Decoding Without a Drafter-Side KV Cache
Parallel Inference without Drafter-Side KV Cache: H-Spec's Hybrid Speculative Decoding TL;DR shows that the bottleneck in concurrent serving is that a block-diffusion…
Analytical Power-Aware Provisioning for Prefill-Decode Disaggregated AI Inference
Analytical PD-inference provisioning uses instance counts and KV-cache reservations to find the lowest-power deployment for a target capacity.
VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attention
VC-Attention is a training-free kernel that removes value-quantization and softmax bottlenecks in low-bit video-DiT attention, speeding it up 1.59× on B200.
Fathom: Per-Query Read Depth for Sparse Decoding over Offloaded KV Caches
Fathom: Accelerating 1M-Token Decoding by 1.67x with Query-Adaptive Depth Scanning TL;DR When agent sessions stretch to 1M tokens and dozens of sessions reside…
The Other Half of the Memory Wall: Serving 35B MoEs from SSD with Trained Routing Prediction
Waking the MoE on SSD: Serving a 35B MoE at 20 tok/s on a 24 GB Desktop with Edge0 One-line summary (TL;DR) Even at 4-bit, a 35B-class MoE occupies 19.5 GB and cannot…
Cache-Aware Joint Router Adaptation for Memory-Efficient MoE Inference
Cache-Learning Routers: Cache-Aware Joint Router Adaptation for Memory-Constrained MoE Inference TL;DR Starting from the observation that MoE's real bottleneck is not…