How the monitored publications were assessed

Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.

23 items read as adverse

• Representation Alignment from a Few Paired Data via Distilled Optimal Transport
  -60 arXiv cs.AI 2026-10-12 low agreement · ±120
• AI’s mathematics blitz pushes science into strange new territory
  -57 The Economist: Science and Technology 2026-10-12 low agreement · ±100
• Autonomous AI Agents Systematically Diverge From Human Preferences in Proof Formalization
  -55 arXiv cs.AI 2d ago low agreement · ±110
• The Helpful Agent Problem: When Emergent Cooperation Among LLM Agents Bypasses Intended Workflows
  -51 arXiv cs.AI 13d ago moderate agreement · ±30
• Democratic governors elected on promises to stop data centre building
  -50 Financial Times: Artificial Intelligence 4d ago single model
• Seq@K: Evaluating Language Models Under Sequential Feedback
  -50 arXiv cs.AI 8d ago low agreement · ±100
• Lessons from Luck: Do LLM-Written Lessons Carry Chance into an Agent's Next Decision?
  -50 arXiv cs.LG (Machine Learning) 11d ago single model
• SimHack: Predicting the onset of detectable reward hacking before RL training
  -50 arXiv cs.LG (Machine Learning) 2026-10-22 single model
• Inside the long, bitter fight over one man’s quest to build the biggest AI datacenter in California
  -50 The Guardian: Artificial Intelligence 2026-10-17 single model
• Proof-based general-purpose computing with Magnetar
  -50 Microsoft Research 2026-10-15 low agreement · ±150
• Harness^2: Recursive Agent Harnessing for an Open World
  -50 arXiv cs.AI 2026-10-15 low agreement · ±150
• SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire
  -50 arXiv cs.AI 2026-10-12 single model
• Stronger artificial intelligence breakthroughs hasten their own exhaustion
  -48 arXiv cs.CY (Computers and Society) 2026-10-21 low agreement · ±100
• When Reality Outpaces Cognition: A New Scaling Principle for Reliable Intelligence
  -40 arXiv cs.AI 2026-10-16 low agreement · ±150
• Hidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication
  -37 arXiv cs.AI 2026-10-23 low agreement · ±150
• A thousand fewer paths to root
  -34 OpenAI 4d ago low agreement · ±110
• Feature Elicitation for SAE Steering of Deceptive Behaviour in Small LLMs
  -33 arXiv cs.LG (Machine Learning) 2026-10-16 low agreement · ±80
• Open-world AI: a Tale of Three Requirements
  -32 arXiv cs.AI 2026-10-16 low agreement · ±105
• Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence
  -31 arXiv cs.AI 2026-10-15 low agreement · ±175
• AI companies want to become frontier scientific researchers
  -30 The Economist: Science and Technology 2026-10-14 low agreement · ±110
• Can a System-One LLM Perform Knowledge Tracing When Few or No Learners Are Logged?
  -26 arXiv cs.CY (Computers and Society) 2026-10-09 low agreement · ±175
• Zuckerberg says Meta has reached AI ‘frontier’ and rejects calls for slowdown
  -26 Financial Times: Artificial Intelligence 2026-10-12 low agreement · ±105
• The Harness as the Only Mutable Surface: Compliance-Bounded Self-Evolution of LLM Agents in Credit Pipelines, with a Measured Admission Gate
  -23 arXiv cs.AI 2026-10-09 low agreement · ±120

Across the whole window

The two tables below describe every item in the last 30 days under scaling. They are deliberately not narrowed by the reading filter (currently adverse), because a mean taken only over items already selected for their score would just restate the filter.

By topic

By source

A source's mean says how the items it published were read. It is not a rating of the source.