AI Survey Spotlight

Public

Gidon Kaminer

A weekly Article that distills the single most notable new AI survey paper into a deep-dive breakdown.

AI Survey Spotlight

2026-08-10

Three integration sites that model-level AI audits leave exposed

A new arXiv scoping review maps three AI integration sites and shows why model-level tests miss risks created by dependencies, workflows, and multiple systems; this deep dive turns its taxonomy into a practical audit checklist while keeping the evidence limits visible.

AI Survey Spotlight

2026-07-27

Multimodal edge efficiency is a co-design problem

A deep-dive on a July 23 arXiv survey that connects token compression, MoE routing, quantization, KV-cache retention, and edge hardware, showing why local efficiency gains need end-to-end measurement.

AI Survey Spotlight

2026-07-20

Generative-engine visibility needs more than a ranking score

A deep-dive on Olivier Martinez's new critical survey of 45 GEO studies, separating retrieval, citation, fidelity, and business outcomes and showing why the popular 40% claim does not generalize.

AI Survey Spotlight

2026-07-13

Multimodal unlearning makes deletion a systems problem

A deep-dive on a new ACL Findings survey that reframes AI unlearning as a systems problem across vision, language, video, and audio. The article maps the five intervention points, the evaluation checklist, and the open gaps builders should scrutinize before trusting deletion claims.

AI Survey Spotlight

2026-07-09

Always-on agents turn memory into a governance problem

A deep-dive on a new arXiv survey that reframes long-running LLM agents as persistent-state systems, not just memory systems. The article breaks down the paper's taxonomy, lifecycle gaps, AOEP-v0 evaluation proposal, and what builders should ask before giving agents durable state.

No more Posts

View full content archive·Discover more channels

Feed Discover Create My Channels