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We release the evaluation subsets, scoring code, and an interactive dashboard at this https URL so the protocol can audit any structure-preserving transform
from the top result below
https://arxiv.org/list/cs.AI/new
We demonstrate that it can self-assemble functional circuits from scratch and rapidly re-route logic around permanent, previously unseen hardware faults
https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks
https://arxiv.org/list/cs.CV/new
CV)
Fine-grained wildlife classification in aerial imagery is limited not only by model performance, but also by unreliable labels: animals occupy few pixels, key visual cues vary seasonally, and modality-specific evidence can be ambiguous
https://arxiv.org/html/2511.06451v1
Spectral safety and discrete Green kernel
https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts
https://arxiv.org/list/cs.SE/new
AI)
Large language models (LLMs) can translate natural-language optimization problems into solver-ready formulations, but direct code generation is brittle: schema, indexing, and semantic errors can cause compilation failures, infeasible models, or incorrect objectives, while iterative repair, search, and multi-agent
https://arxiv.org/html/2609.03371v1
Operators can replace or upgrade their instruments and distribute longitude coverage across a network
https://arxiv.org/html/2607.27099v1
The statistical inference methodology we introduce can identify critical cluster processes at small scales while recovering the signature of this criticality on coarser scale data obtained from other measurement sources
https://arxiv.org/list/econ/new
The paper develops a mechanism-design model showing that the same delegated intermediation structure can generate both Stiglitz-Weiss underinvestment and De Meza-Webb overinvestment distortions
https://arxiv.org/html/2608.02613v1
A benchmark for personal memory in this setting should therefore evaluate the full stack on device, not just whether a model can retrieve the relevant information
https://arxiv.org/list/cs.CR/new
We also show that coarse-to-fine label selection can create near-perfect measured correlation without learned dependence
https://arxiv.org/html/2608.02817v1
seminar participants at the NBER 2024 SI (ME), UC Berkeley, Boston College, the University of Maryland, the Federal Reserve Board of Governors, the Federal Reserve Banks of Atlanta, Boston, Chicago, and Richmond, ITAM, IMF, Banque de France, BIS, Bocconi, EIEF, CREI, the University of Iowa, Georgetown University, PUC
https://arxiv.org/list/quant-ph/new
While the mathematical structure of matrix product states (MPS) is well understood through the MPS fundamental theorem, an analogous understanding for mixed-state tensor networks remains largely absent: if two purification tensors generate the same density matrix, how are they related
https://arxiv.org/list/cs.OS/new
Linux provides several ways to observe and respond: Pressure Stall Information (PSI) can detect memory-related task stalls, zram can provide compressed in-memory swap space, and cgroup v2 can request memory reclamation within a selected control group
https://arxiv.org/abs/2608.12700
We build the instrument that checks correctness properly: a contract-grade verifier of twelve adversarial gates, each a property a correct kernel must satisfy, several of them tolerance-free, so no choice of threshold can explain a failure away
https://arxiv.org/abs/2204.04218
In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques capture several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results
https://arxiv.org/list/cs.DB/new
We propose an architectural pattern for such systems, a trusted kernel with a generative shell, resting on one invariant: a component that can fabricate may influence which question the system answers, never which value it returns
https://arxiv.org/abs/2608.02851v1
The design relies on two affine Volterra transformations involving both Fredholm- and Volterra-type integral terms, which results in a four-PIDE kernel equations
https://arxiv.org/abs/2512.09590
Using an extension of the exponential-affine transformation formula for those processes, we establish in the long run the existence of limiting distributions, which (unlike in the case of classical affine diffusion processes) may depend on the initial state of the process, unless the Volterra kernel coincides with the
https://arxiv.org/abs/2608.01651
We present Bole, a kernel--runtime co-design that enables efficient tree speculation for hybrid-attention LLMs
https://arxiv.org/html/2608.02851v1
Although several related problems can be transformed into comparable forms [redaud2022stabilizing], they do not directly address the PIDE setting considered here
https://arxiv.org/abs/2504.02246
Despite advances in verification tooling, conventional programmers are rarely involved in the verification of their own code, resulting in higher development and maintenance costs for verified software
https://arxiv.org/abs/1202.3424
, dust particles), but may also be 1-d or 2-d periodic arrays of "target unit cells", which can be used to study absorption, scattering, and electric fields around arrays of nanostructures
https://arxiv.org/list/cs.DC/new
SE)
Automating GPU kernel optimization remains difficult in practice: generated variants can violate correctness constraints, runtime measurements are noisy, and search often stalls early
https://arxiv.org/abs/2609.14858
Our key insight is that accumulated discovery history can serve as a replay simulator over the realized search space
https://arxiv.org/html/2609.02852v1
However, various strands of evidence indicate that an LLM’s externalized linguistic outputs and mechanistically-extracted linguistic features can be an unreliable lens for understanding internal model computation
https://arxiv.org/list/math.ST/new
If \(T_\star\) is the selected physical trajectory length and \(a_\star=\sqrt m\,T_\star\), a terminal-depth transfer argument yields restricted conductance and warm-start mixing without lazifying either kernel
https://arxiv.org/html/2608.02612v1
Recent studies have therefore examined how to automatically derive optimization problems from natural-language descriptions, but existing benchmarks focus on settings where objectives and constraints can be written explicitly as mathematical expressions
https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other]
Title: Warped Kernel Estimator for I
https://arxiv.org/html/2508.20101v1
In an empirical application, we demonstrate how the model can be applied to financial stock networks