AI Explained
Plain explanations of trending AI concepts, with live visualizations.
LACUNA tests whether LLM unlearning hits the right weights — Output-level vs weight-level unlearning evaluation — What does it mean?
LACUNA plants a fact in known weights to test whether unlearning erases it, or just hides the output while a resurfacing attack revives it.
Google releases TabFM for zero-shot tabular prediction — Tabular in-context learning — What does it mean?
TabFM predicts on a spreadsheet it has never seen by reading the whole table as one prompt — in-context learning, no per-dataset training.
BlockSearch traces million-token retrieval collapse — Attention dilution — What does it mean?
BlockSearch traces long-context retrieval collapse to attention dilution — the softmax denominator drowning the gold document — and fixes it with a length-aware softmax.
Orca learns a unified world model over video and events — Next-State-Prediction — What does it mean?
Orca trains one shared world model with a single objective — predict the next state — then reads it out as text, image, or action.
CausalMix picks LLM pretraining data mixtures via causal inference — CATE-based data mixture selection — What does it mean?
CausalMix picks an LLM's pretraining data mix by causal inference: estimate each mix's causal effect from 512 tiny runs, then scale to 7B.
ELDR routes MoE decode by expert locality, cutting TPOT up to 13.9% — Expert-locality-aware decode routing — What does it mean?
ELDR predicts a request's experts and routes decode to the worker whose zone matches, so fewer experts reload — cutting TPOT 5.9–13.9%.
DOPD dodges the 'privilege illusion' — Dual on-policy distillation — What does it mean?
DOPD routes each token's distillation signal by advantage, so a small model learns real skill instead of an answer key it can never hold.
BlockPilot gives diffusion speculative decoding 4.2× — Instance-adaptive draft block sizing — What does it mean?
BlockPilot learns a per-input policy that predicts the best draft block size for diffusion speculative decoding, hitting 4.20× on a 4B model.
MultiHashFormer drops the vocab-sized embedding table — Hash-signature token representation — What does it mean?
A new LM names each token by a short multi-hash signature instead of a vocab-sized embedding row, decoupling parameters from vocabulary size.
Cluster-Route-Escalate cascade serves LLMs at 97-99% accuracy for less cost — Cost-aware LLM cascade — What does it mean?
A cascade routes each query to the cheapest capable model and escalates only weak answers to a stronger one: 97-99% accuracy at lower cost.
SGLang v0.5.14 — LPLB expert-parallel load balancing — What does it mean?
SGLang v0.5.14's LPLB solves a tiny linear program each step to even MoE token load across GPUs, so the busiest GPU stops gating throughput.
ViQ: text-aligned visual tokens, quantized at any image resolution — Text-aligned quantized visual tokens vs continuous patches — What does it mean?
ViQ turns images into discrete, text-aligned visual tokens — like a fixed vocabulary of labeled stamps — so a multimodal LLM reads pictures the way it reads words, at any resolution.
