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How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science
Announce Type: replace-cross Abstract: Every generative model for crystalline materials harbors a critical structure size beyond which its outputs become unreliable; we call this the extrapolation frontier. Despite its consequences for nanomaterial design, this frontier has never been systematically measured. We introduce RADII, a radius-resolved benchmark of ~75,000 crystal-derived nanoparticle structures (33-11,298 atoms) that treats radius as a continuous scaling knob, tracing generation...
How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science
Announce Type: replace-cross Abstract: Every generative model for crystalline materials harbors a critical structure size beyond which its outputs become unreliable; we call this the extrapolation frontier. Despite its consequences for nanomaterial design, this frontier has never been systematically measured. We introduce RADII, a radius-resolved benchmark of ~75,000 crystal-derived nanoparticle structures (33-11,298 atoms) that treats radius as a continuous scaling knob, tracing generation...
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
arXiv:2606.06547v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a "stability lag" where early decisions remain fragile even after being written. We reveal that Post-Training Quantization (PTQ) error easily flips these borderline decisions at the write frontier, which are then permanently locked in and amplified. To address this, we propose Frontier-Aware Instability-Reweighted Calibration (FAIR-Calib),...
Think Fast: Estimating No-CoT Task-Completion Time Horizons of Frontier AI Models
arXiv:2606.07157v1 Announce Type: new Abstract: Many efforts to ensure frontier AI models are safe rely on monitoring their chain-of-thought (CoT) reasoning. If models become able to perform sufficiently complex reasoning internally, without explicit thinking tokens, this would undermine such oversight. We measure how well frontier models reason without CoT across a suite of over 30,000 questions spanning 43 benchmarks in domains including math, coding, puzzles, causality, theory-of-mind,...
Zero knowledge verification for frontier AI training is possible
arXiv:2606.05433v1 Announce Type: new Abstract: Frontier AI governance frameworks increasingly use cumulative training compute as the primary criterion for designating high-impact models, but enforcement rests on self-reporting because no technical verification primitive for training exists. Any future international agreement on frontier AI faces the same problem at higher stakes: coordinated regulation of technologies with significant externalities has historically rested on technical...
BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution
arXiv:2606.01286v1 Announce Type: new Abstract: The rapid progress of frontier large language models has led to widespread benchmark saturation, limiting the ability of existing datasets to differentiate model capabilities or provide useful training signal. For instance, on LiveCodeBench, frontier models achieve over 99% Pass@1 on easy splits and exceed 90% Pass@1 on average across difficulty levels.
Frontier passengers tackle man who allegedly choked off-duty flight attendant, tried to open door mid-flight
Federal officials have filed charges against the man accused of assaulting a flight attendant and trying to escape a Frontier Airlines plane before passengers pinned him down while the plane was en route to Chicago earlier this week. Juan Gabriel Reyes, 51, of Chicago, is charged with interference with flight crew members and attendants, and assault within maritime territorial jurisdiction, the U.S. Attorney's Office for the Southern District of Florida announced Wednesday. Court records...
Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures
arXiv:2604.03042v2 Announce Type: replace Abstract: Multi-agent autonomous exploration is essential for applications such as environmental monitoring, search and rescue, and industrial-scale surveillance. However, effective coordination under communication constraints remains a significant challenge. Frontier exploration algorithms analyze the boundary between the known and unknown regions to determine the next-best view that maximizes exploratory gain.
Beyond the Frontier: Stochastic Backtracking for Efficient Test-Time Scaling
arXiv:2605.25143v2 Announce Type: replace Abstract: Test-time scaling improves language model reasoning by spending additional compute to explore multiple solution trajectories. The key challenge is to maximize accuracy while minimizing the total number of generated tokens during reasoning. Recent PRM-guided methods score intermediate prefixes to steer this search, but most are frontier-only: they keep only the current active prefixes and irreversibly prune or resample away the rest using...
xAI is looking more like a datacentre REIT than a frontier lab
xAI is looking more like a datacentre REIT than a frontier lab An unexpected development over the past few weeks is xAI's new partnerships with Anthropic and Google, providing them with a huge amount of capacity. It's worth remembering that xAI is now part of SpaceX, after the two merged back in February - so the revenue from these deals flows straight into the entity about to go public. While much has been made of the potential financial engineering given SpaceX's upcoming IPO, I think...