Hidden birth event information restores identifiability to time-dependent birth-death phylodynamic models; mutation-at-birth models make sequences sufficient to recover it.
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16 Pith papers cite this work. Polarity classification is still indexing.
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2026 16representative citing papers
AI-only technical discourse on MoltBook is coherent and organized around 12 themes led by security and trust, but it lacks the concrete code, runtime failures, and reproduction steps common in human GitHub discussions.
Zombie domain linkages persist after ownership changes in DNS integrations at rates of 3% in Web PKI, 24% in ENS, and 15% in Maven Central, with validate-once designs accumulating long-term risks while per-use validation prevents them.
The profile maximum likelihood estimator for the location in anisotropic hyperbolic wrapped normal models is strongly consistent, asymptotically normal, and attains the Hájek-Le Cam minimax lower bound under squared geodesic loss.
A large-scale study of real-world repositories finds that AI-generated code differs from human-written code in complexity, structural traits, defect indicators, and commit-level activity patterns.
Semantic segmentation decomposes monitoring features into canonical and residual components that concentrate fault-predictive information while preserving operational meaning in predictive maintenance.
A functional central limit theorem for pattern frequencies in 2D samples enables nonparametric goodness-of-fit, two-sample, and symmetry tests for copulas, with bootstrap critical values and parametric examples.
Joint location-scale minimization for geometric medians on product manifolds degenerates to marginal medians, and three new scale-selection methods restore identifiability with asymptotic guarantees.
MONET represents tasks as graph nodes and uses neighbor-based crossover plus per-task mutation to transfer knowledge, matching or exceeding MAP-Elites performance on four large-scale simulation domains.
RISE applies CountSketch to dual lexical and semantic channels derived from output-layer gradient outer products, cutting data attribution storage by up to 112x and enabling retrospective and prospective influence analysis on LLMs up to 32B parameters.
The SSTN detects non-normality by tracking how the standardized empirical characteristic function changes under repeated self-similarity transformations, with the null distribution calibrated by Monte Carlo simulation.
Four LLMs exhibit a shared implicit social policy that under-allocates pensions by a factor of three and over-allocates housing by four compared to OECD budgets, with only Claude showing meaningful response to national context.
Mixed-precision SSA with stochastic rounding preserves ensemble statistics across five biological models while cutting memory use by 2-4x and delivering up to 1.5x CPU speedup.
sumoITScontrol provides a collection of traffic controllers for SUMO simulations and stresses the importance of variance-aware evaluation methods for reproducible research.
Football fever in spectators follows a V-shaped time course captured as a latent process from heart rate and stress data via time-dependent structural equation modeling.
This work provides an empirical comparison of tool integration, multi-agent delegation, and hybrid architectures for LLM task orchestration, measuring response time, context consumption, cost, error recovery, and implementation complexity.
citing papers explorer
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Information on hidden birth events restores identifiability in phylodynamic inference
Hidden birth event information restores identifiability to time-dependent birth-death phylodynamic models; mutation-at-birth models make sequences sufficient to recover it.
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What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook
AI-only technical discourse on MoltBook is coherent and organized around 12 themes led by security and trust, but it lacks the concrete code, runtime failures, and reproduction steps common in human GitHub discussions.
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Zombies in Alternate Realities: The Afterlife of Domain Names in DNS Integrations
Zombie domain linkages persist after ownership changes in DNS integrations at rates of 3% in Web PKI, 24% in ENS, and 15% in Maven Central, with validate-once designs accumulating long-term risks while per-use validation prevents them.
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Profile Likelihood Inference for Anisotropic Hyperbolic Wrapped Normal Models on Hyperbolic Space
The profile maximum likelihood estimator for the location in anisotropic hyperbolic wrapped normal models is strongly consistent, asymptotically normal, and attains the Hájek-Le Cam minimax lower bound under squared geodesic loss.
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A Large-Scale Empirical Study of AI-Generated Code in Real-World Repositories
A large-scale study of real-world repositories finds that AI-generated code differs from human-written code in complexity, structural traits, defect indicators, and commit-level activity patterns.
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Semantic Feature Segmentation for Interpretable Predictive Maintenance in Complex Systems
Semantic segmentation decomposes monitoring features into canonical and residual components that concentrate fault-predictive information while preserving operational meaning in predictive maintenance.
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Pattern-based tests for two-dimensional copulas
A functional central limit theorem for pattern frequencies in 2D samples enables nonparametric goodness-of-fit, two-sample, and symmetry tests for copulas, with bootstrap critical values and parametric examples.
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Scale selection for geometric medians on product manifolds
Joint location-scale minimization for geometric medians on product manifolds degenerates to marginal medians, and three new scale-selection methods restore identifiability with asymptotic guarantees.
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Multi-Task Optimization over Networks of Tasks
MONET represents tasks as graph nodes and uses neighbor-based crossover plus per-task mutation to transfer knowledge, matching or exceeding MAP-Elites performance on four large-scale simulation domains.
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Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation
RISE applies CountSketch to dual lexical and semantic channels derived from output-layer gradient outer products, cutting data attribution storage by up to 112x and enabling retrospective and prospective influence analysis on LLMs up to 32B parameters.
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A test for normality based on self-similarity
The SSTN detects non-normality by tracking how the standardized empirical characteristic function changes under repeated self-similarity transformations, with the null distribution calibrated by Monte Carlo simulation.
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Social Policy of Large Language Models: How GPT, Claude, DeepSeek and Grok Allocate Social Budgets in Spain and Germany
Four LLMs exhibit a shared implicit social policy that under-allocates pensions by a factor of three and over-allocates housing by four compared to OECD budgets, with only Claude showing meaningful response to national context.
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Reduced-Precision Stochastic Simulation for Mathematical Biology
Mixed-precision SSA with stochastic rounding preserves ensemble statistics across five biological models while cutting memory use by 2-4x and delivering up to 1.5x CPU speedup.
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sumoITScontrol: Traffic Controller Collection for SUMO Traffic Simulations
sumoITScontrol provides a collection of traffic controllers for SUMO simulations and stresses the importance of variance-aware evaluation methods for reproducible research.
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Time-dependent structural equation modeling of fans' football fever using activity tracking data during the 2025 DFB Cup final
Football fever in spectators follows a V-shaped time course captured as a latent process from heart rate and stress data via time-dependent structural equation modeling.
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Empirical Comparison of Agent Communication Protocols for Task Orchestration
This work provides an empirical comparison of tool integration, multi-agent delegation, and hybrid architectures for LLM task orchestration, measuring response time, context consumption, cost, error recovery, and implementation complexity.