AI Explained

Plain explanations of trending AI concepts, with live visualizations.

LLM

CoWindow Attention splits distant history across heads — Complementary per-head windows — What does it mean?

Each KV head keeps the recent window but watches only its own slice of the far past; together the heads still see every token.

LLM

SANTA++ uses 16–22% of dense KV reads — Inverse-probability sampled attention — What does it mean?

SANTA++ samples groups of cached keys and reweights each by 1/p, estimating full attention from 16–22% of the KV reads.

LLM

KV-streams — Keeping the KV cache through context compaction — What does it mean?

Delete old KV-cache entries in place instead of starting a fresh trace, so compaction never re-prefills the kept context.

LLM

Allocate low-bit recurrent state precision by channel decay — Decay-aware bit allocation for recurrent states — What does it mean?

A rounding error in a recurrent state lasts as long as its row remembers, so slowly decaying rows get more bits at the same average.

LLM

CacheReforge — Stale KV cache repair after LoRA adapter updates — What does it mean?

A LoRA update makes cached K/V stale. CacheReforge recomputes about 5% of layers instead of half and removes 92% of the output drift.

LLM

Reparameterize output heads before W4 quantization — Softmax-preserving head shift — What does it mean?

Softmax ignores shared logit shifts, so choosing an equivalent output head before rounding can make a 4-bit head far more faithful.

LLM

Crossflow — Revocable decode-node leases — What does it mean?

Let decode GPUs lend short-lived, revocable capacity to prefill when prompt demand spikes, instead of re-splitting a fixed P/D cluster.

LLM

From Memory Budgets to Risk Targets — Risk-controlled KV cache eviction — What does it mean?

Pick how much KV cache to evict by certifying how often requests break, not by average score, and keep the full cache if nothing passes.

LLM

Greedy decoding is not precision-invariant — Top-two logit margin decides BF16 vs FP16 flips — What does it mean?

Same model, same prompt, greedy decoding: BF16 and FP16 still disagree, and a tiny top-two logit margin decides where.

LLM

CompKV sparse attention paper — Compensation-aware KV block selection — What does it mean?

CompKV picks which KV blocks sparse attention reads exactly by the error a block-mean stand-in would leave: mass times logit variance.

LLM

Tree speculative decoding on DeepSeek-V4 — Branch-isolated compressed state — What does it mean?

Tree speculation on compressed attention needs a temporary state per branch and a commit of only the accepted path.

LLM

KV-COBRA splits the KV-cache budget per head — Rank vs bit-width allocation — What does it mean?

KV-COBRA picks rank and bit width per attention head instead of globally, so the same KV-cache bits land where they cut the most error.