2026-09-16

Both picks score 1.85 and the tie is real — base 1.3 × agents 1.5, −0.1 each, with nothing in interests.md able to separate them. This is the fourth distinct scoring collision recorded in fifteen days; as on 09-09, 09-11, 09-12 and 09-15, no weight was adjusted mid-run.

When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis — arXiv 2609.15309 (1.85)

• TL;DR: track the best solution found at each token budget, aggregate within-task orderings into Elo via Bradley-Terry, and compare against independent sampling, whose Elo grows linearly with log compute. Four general-purpose agents on four open-ended benchmarks, sessions to 100M tokens: they convert tokens into Elo faster than the reference at first, diminish, and eventually fall below it. The crossover is named the scaling inflection point
• Why read it: it is a prescription, not just a diagnosis. Splitting 100M tokens into parallel sessions sized at that point gained +264 Elo over one long session and +355 over ten short ones on FrontierCS Polyomino Packing
• The decaying thing is the scaffold, which is why it lands on Agents (LLM Agents) as much as on Test-Time Compute (Inference-Time Compute Scaling): an agent revising, exploring and deciding when to stop is what eventually underperforms sampling and keeping the best. The strongest human contestants, on shared AtCoder Heuristic Contest tasks, improve superlinearly — differently shaped curves on the same tasks, and the human one keeps bending upward
• Neither the four agents nor the four benchmarks is named, no inflection value is published for any of them, and the +264 / +355 pair comes from one task
• → When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis (new)

Atria Dawn: The Dawn of Agentic Superintelligence — arXiv 2609.15818 (1.85)

• TL;DR: an agentic foundation model trained through a Verifiable Experience Pipeline — tool-mediated interactions against executable environments and externally verified outcomes — reporting 16 benchmarks, the highest reported score on five, and "competitive" elsewhere. Published alongside a study of 769 task records from 56 participants in its own development: about one-third of completed AI-assisted tasks were rated infeasible without AI, and agents "frequently propose methods and implement revisions" while humans "retain most final decisions"
• Why read it: Frontier Pacing's only figure of this shape is OpenAI's 3.1 agent-workdays per human workday, which is an input measure with no output attached and no published methodology. This is the output side, with a stated denominator — and it is a self-study: the raters built the system they rate, and no control, blind condition or external replication appears in anything read
• A paper titled for superintelligence closes by asking for human oversight, arguing progress must advance "both the capacity for discovery and the capacity for meaningful human oversight, preserving accountable human authority". "Most final decisions" is not a number, which is the same gap AI Control Roadmap keeps arriving at
• No lab, author, weights, licence, parameter count or benchmark list is published — for a paper whose central evidence is an internal labour study of its own team, the missing affiliation is material rather than clerical
• → Atria Dawn: The Dawn of Agentic Superintelligence (new)

• Step 3 may have a meeting date, and this wiki has no record of it. Chasing a Trivium China item on China's AI-safety positions surfaced a Reuters report of 2026-09-04 that the US and China are preparing a mid-September AI safety dialogue, with Treasury Secretary Scott Bessent leading the US delegation, following the May 2026 Trump–Xi summit. Frontier Pacing records step 3 — bargaining with authoritarian governments — as having no taker, and a scheduled bilateral is the nearest thing to a counterparty this argument has had. Nothing read establishes that it happened, what was discussed, or that pacing was on the agenda, so no page was changed. Bessent appears on AI Governance only in the July distillation-sanctions context
• Three recursive-self-improvement papers landed in one 25-entry snapshot, in the week RSI is the stated first reason for slowing down. Besides today's second pick: 2609.14858 Dream-RSI, self-improving exploration via a replay simulator built from historical discovery trees, and 2609.15364 RSIAgent, whose frozen memory is stated to let Kimi K3 and GLM-5.3 outperform GPT-6 on OSWorld-v2 and Agent's Last Exam. Neither was given a page; both are cited to the snapshot rather than wikilinked, so nothing links to a page that does not exist. Nothing read connects any of them to the pacing argument — the cluster is the observation
• A cheapest-inference claim was reported to be a resale, and this repo has a script that assumes exactly that problem. A r/LocalLLaMA thread (prefetch #41, 2026-09-15) reports CrofAI, advertised as the world's cheapest inference provider, exposed as an OpenRouter wrapper. CLAUDE.md already documents why spec-check compares against the first-party provider's endpoint rather than a catalogue headline — GLM-5.2 alone is served by 33 providers between $0.72 and $2.31 on input. Single-thread sourcing, so no page was changed; flagged against Model Routing

Created today. Flagged for your review.

• AI Evaluator Forum (AEF) (new — entity page, review recommended)
• Gemini 3.8 Live (new)
• Gemini 3.8 Live Extended Thinking (new)
• When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis (new)
• Atria Dawn: The Dawn of Agentic Superintelligence (new)

The +0.3 applied once. AI Evaluator Forum (AEF) is a genuinely new entity; the two model pages are not entity or concept pages, so the "new entity/concept page needed" adjustment does not reach them, which is the literal reading interests.md supports and the same reading the 09-11 and 09-15 runs made.

• Frontier Pacing — new section on the Forum and AEF-1, Open Problem 1 advanced (a forum and a body now exist, and neither answers steps 2 or 3), and a new ## Conflicting Reports entry on whether three labs cosigned the standard
• Google DeepMind — the two Live models added to Models & Products, plus a Recent Activity entry recording that the standards body its own reply pointed to had existed since December and that DeepMind is in neither founding-member list
• Agents (LLM Agents) — both papers added to Key Papers / Events
• Test-Time Compute (Inference-Time Compute Scaling) — Elo-per-token added to Key Papers; the page's first published stopping point rather than another scaling result
• index.md — five new lines