Safety · Concept

Inference-Time Alignment via Probabilistic Model Blending

BlendIn framework improves inference-time alignment by creating hybrid distributions that weight guidance reliability, reducing excessive interventions.

Trend strength 2/10

Momentum +2/q

Confidence low

Status new

Forecast horizon

Connections

Connections · 1

How this node ties into the rest of the map, and the evidence behind each link.

to · applies to 3/10

RLHF Shallow Alignment and Partisan Structure Preservation

Inference-time alignment via BlendIn addresses limitations of RLHF-based alignment by providing quality-aware guidance at deployment time.

+3 growth

Signal sources

Dated facts from primary sources in this direction.

US evaluation centre Jun 2025

In June 2025 the US AI Safety Institute was renamed the Center for AI Standards and Innovation (CAISI), pivoting toward security, standards and adversary-model assessment.

NIST →

Frontier safeguards May 2025

Anthropic activated its ASL-3 deployment and security standard with Claude Opus 4 on 22 May 2025 — the first real-world trigger of a responsible-scaling tier, focused on blocking bio-weapon uplift.

Anthropic →

Cross-border testing 2025

The International Network of AI Safety Institutes (launched Nov 2024) ran a third joint testing exercise focused on agentic AI systems across cyber and fraud strands.

European Commission — AI Office →