Fetching from the wire…
01
02
03
04
05
06
07
08
Public story · 2026-03-19 · source-backed
ArXiv 2603.17368 proposes evaluating safety policy before chain-of-thought generation rather than after. Models that reason first and apply safety second can be manipulated through the reasoning trace itself. Reordering substantially improves alignment without degrading benchmarks. Directly relevant as frontier reasoning models become defaults for agentic deployments. arXiv
Each link below shares sources, entities, or timing with this story.
ArXiv paper 2603.14805 argues the primary bottleneck in scaling agentic development is knowledge architecture — "skills" (composable, governance-aware units encoding institutional knowledge) are the right primitive for agents, not raw docs or in-context retrieval. Directly rel...
ArXiv 2603.17310 introduces training rewards based on AUC of information gain across reasoning steps rather than final-answer correctness. Directly targets "reasoning theater" where extended chain-of-thought adds tokens without proportional accuracy gains. Compatible with exis...
This paper derives the "1/W law": tokens per watt halves every time effective context window doubles. Translation: which GPU services which context is a more powerful energy lever than buying newer GPUs. For large-context agentic deployments, your routing architecture matters...
arXiv 2608.05086, billed as the largest psychometric analysis of LLM safety evals to date, finds three interpretable factors (refusal strictness, truthfulness, contextual harm) explain most between-model variance. Psychometrically selected items recover full benchmark scores w...
This paper models LLM training as information transmission over a noisy channel via the Shannon-Hartley theorem. Existing power-law scaling laws can't explain catastrophic overtraining or quantization-induced degradation. This framework predicts when scaling breaks down. Direc...
Policy Compiler for Secure Agentic Systems introduces deterministic enforcement — a reference monitor intercepts all agent actions and blocks violations before execution. Compliance jumps from 48% to 93% across frontier models with zero violations in instrumented runs. Directl...
MindPattern daily
One email a day at 7 AM. Sources and a take on every story. Unsubscribe anytime.