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L$^3$: Large Lookup Layers
arXiv:2601.21461v3 Announce Type: replace Abstract: Modern sparse language models typically achieve sparsity through Mixture-of-Experts (MoE) layers, which dynamically route tokens to dense MLP "experts." However, dynamic hard routing has a number of drawbacks, such as potentially poor hardware efficiency and needing auxiliary losses for stable training. In contrast, the tokenizer embedding table, which is natively sparse, largely avoids these issues by selecting a single embedding per token...
Global exponential stability for the three-dimensional Navier-Stokes equations on hyperbolic space
Announce Type: replace-cross Abstract: We prove that the three-dimensional incompressible Navier-Stokes equations with the deformation Laplacian on hyperbolic 3-space $\HH^3$ admit a unique global mild solution for sufficiently small initial data in $L^3(\HH^3)$, and that this solution decays exponentially to zero. The exponential decay rate is $\mu\lambda_\Def^{(3)}$, where $\mu$ is the dynamic viscosity and $\lambda_\Def^{(3)} = 26/9$ is the effective spectral gap of the deformation...
Which Defense Closes Which Threat? Attributing OWASP-LLM-Top-10 Coverage and Its Brittleness Under Paraphrasing
arXiv:2606.02822v1 Announce Type: new Abstract: Production LLM applications stack several defense families -- refusal-phrase filters, token-budget controls, model allowlists, rate limits, tool-registry authentication -- yet existing breach-and-attack-simulation (BAS) benchmarks report a single aggregate coverage number, hiding which family closes which threat. We measure attribution. We add four OWASP-LLM-Top-10-aware agents to a 21-agent baseline scanner and target a lattice of four...
Dmitry Bivol reclaims top spot at light heavyweigh...
Dmitry Bivol returned to the rankings after a 15-month absence, reclaiming the No. 1 spot at light heavyweight with a dominant performance against Michael Eifert . The fight was less about the opponent and more about Bivol knocking the rust off with a one-sided victory that was never in doubt. After knocking down Eifert in the opening round with a left hook, Bivol remained in control to retain the WBA and IBF light heavyweight titles by unanimous decision.
Decentralized Stochastic Nonconvex Optimization under the $(L_0,L_1)$-Smoothness
arXiv:2509.08726v3 Announce Type: replace-cross Abstract: This paper focuses on the decentralized stochastic optimization problem $f(\mathbf{x})=\frac{1}{m}\sum_{i=1}^m f_i(\mathbf{x})$ over a connected network of $n$ agents, where each local function has the form of $f_i(\mathbf{x}) = {\mathbb E}\left[F(\mathbf{x};{\boldsymbol \xi}_i)\right]$ which satisfies the $(L_0,L_1)$-smooth condition but possibly nonconvex and each random variable ${\boldsymbol \xi}_i$ follows distribution ${\mathcal...
US military kills two alleged narco-terrorists in latest Eastern Pacific strike on drug-trafficking vessel
The U.S. military carried out a lethal strike Wednesday on a vessel it said was involved in drug trafficking in the Eastern Pacific, killing two men it described as "narco-terrorists," according to U.S. Southern Command (SOUTHCOM)."On June 3, at the direction of #SOUTHCOM commander Gen. Francis L. Donovan, Joint Task Force Southern Spear conducted a lethal kinetic strike on a vessel operated by Designated Terrorist Organizations," SOUTHCOM said in a post on X."Intelligence confirmed the...
‘Trump curse’: Knicks fans blame president after MSG loss to Spurs in Game 3
‘Trump curse’: Knicks fans blame president after MSG loss to Spurs in Game 3 Fans already lost out on watch parties near Madison Square Garden due to Trump’s attendance - Bookmark - CommentsGo to comments New York Knicks fans devastated after their team lost to the San Antonio Spurs in Game 3 of the NBA Finals have found a new person to blame — President Donald Trump. The Knicks were on a 13-game winning streak, including the first two games in the best-of-seven series against the Spurs....
A thalamus–brainstem attractor network drives history-biased decisions
Abstract Natural environments often change gradually, making it adaptive to bias decisions on the basis of the recent past — a phenomenon known as serial dependence1,2,3. Large-scale recordings during behaviour have identified that serial dependence is a common motif for decision-making, with neural representations of past experiences found throughout the brain4,5,6,7,8,9,10,11. However, it remains unclear whether this bias arises from dedicated neural circuits with history-specific...
Predicting every game of the entire World Cup: All...
Everyone is using artificial intelligence to do, well, everything. With the World Cup starting on June 11, you can't scroll for more than a couple of minutes without hitting another post or video or reel of someone telling you how they used AI to predict the World Cup. So, I decided to use my own supercomputer to predict every game of the 2026 World Cup -- the supercomputer is called "my brain."
Optimal Bayesian Stopping for Efficient Inference of Consistent LLM Answers
arXiv:2602.05395v2 Announce Type: replace-cross Abstract: A simple strategy for improving LLM accuracy, especially in math and reasoning problems, is to sample multiple responses and submit the answer most consistently reached. In this paper we leverage Bayesian prior information to save on sampling costs, stopping once sufficient consistency is reached. Although the exact posterior is computationally intractable, we further introduce an efficient "L-aggregated" stopping policy that tracks...