Empirical study of LLM brand recommendations across industries finds moderate concentration (mean Gini 0.28) and low cross-model agreement (41.6%) on top brands.
hub
Power-Law Distributions in Empirical Data
18 Pith papers cite this work, alongside 7,604 external citations. Polarity classification is still indexing.
18
Pith papers citing it
7,604
external citations · OpenAlex
hub tools
citation-role summary
background 1
method 1
citation-polarity summary
fields
cs.CL 2 cs.SE 2 astro-ph.EP 1 astro-ph.GA 1 astro-ph.SR 1 cs.CY 1 cs.IR 1 cs.MA 1 cs.SI 1 econ.EM 1years
2026 18representative citing papers
Optimizing environmental and demographic parameters in a JAX-based agent-based model with RNN controllers produces population dynamics resembling Lotka-Volterra cycles using a feature-based loss.
An automated detection method applied to simulated flare ribbon data identifies fine structures whose motions and flux distribution are consistent with plasmoid-mediated reconnection.
Iterated learning theory predicts and LLM experiments confirm non-monotonic compositionality during self-training, reframing model collapse as cultural transmission with matching human regularization patterns.
Bitcoin price power law is rejected on distributional series and not robust to time-origin shifts, but dominates medium-horizon forecasts against baselines because it avoids committing to specific wave shapes.
Factual recall quality in LLMs follows a sigmoid scaling law in the log-linear combination of model parameter count and topic frequency in training data, explaining 60% of variance across models and up to 94% within families.
Empirical analysis of 4707 MoltBook posts shows AI-only technical discourse focuses on security, trust, and abstract topics while lacking concrete runtime and project details found in human GitHub discussions.
Bayesian procedures are derived to compute the posterior probability that a recoverable process is currently in control or that a drifting latent parameter lies in an acceptable region.
The Hall-Sandpile model on WIOD networks generates four ordered regimes of instability where mean avalanche size and large-event probabilities increase with shock intensity and reduced redundancy, without evidence for universal power-law criticality.
ALMA comparison finds starless cores in evolved IRBCs have ~2x higher median mass and density than in early IRDCs, favoring competitive accretion over massive prestellar core models for high-mass star formation.
Inequality in online user engagement, quantified via KL-divergence, inverse coefficient of variation, and log-Gini on bipartite networks, remains stable over time across multiple platforms and interaction types.
Markov chain Phase-Type decoders in VAEs enable heavy-tailed generation where Gaussian decoders fail due to structural limitations from Lipschitz continuity.
Young M dwarf flares exert greater chemical stress on primordial exo-Earth atmospheres than previous models, with potential for lasting changes in mixing ratios especially for low-abundance species.
AI-native software ecosystems exhibit emergent behaviors best explained by complex adaptive systems theory, requiring new ecosystem-level monitoring and seven testable propositions that may extend or replace Lehman's laws.
Review and simulation comparison of more than 40 threshold selection procedures for univariate extreme value analysis, with application to daily rainfall data.
Modeling comparison finds that the Mohr-Coulomb law overestimates maximum escarpment height relative to the modified Griffith criterion, with differences on the order of geological variations.
A literature survey finds no peer-reviewed Bitcoin price models beat the naive baseline at medium horizons and proposes methodological improvements including walk-forward testing and Diebold-Mariano tests.
citing papers explorer
-
Who Owns the AI Recommendation? A Multi-Industry Empirical Map of Brand Category Ownership Across Large Language Models
Empirical study of LLM brand recommendations across industries finds moderate concentration (mean Gini 0.28) and low cross-model agreement (41.6%) on top brands.
-
Tuning Agent-Based Predator-Prey Models Toward Lotka-Volterra Dynamics
Optimizing environmental and demographic parameters in a JAX-based agent-based model with RNN controllers produces population dynamics resembling Lotka-Volterra cycles using a feature-based loss.
-
Automatic detection of Flare Ribbon Fine Structures as Proxies for Plasmoid Dynamics in Flare Reconnection
An automated detection method applied to simulated flare ribbon data identifies fine structures whose motions and flux distribution are consistent with plasmoid-mediated reconnection.
-
Model Collapse as Cultural Evolution
Iterated learning theory predicts and LLM experiments confirm non-monotonic compositionality during self-training, reframing model collapse as cultural transmission with matching human regularization patterns.
-
Bitcoin's Power Law: Weak Structure, Strong Forecasts
Bitcoin price power law is rejected on distributional series and not robust to time-origin shifts, but dominates medium-horizon forecasts against baselines because it avoids committing to specific wave shapes.
-
Predictable Confabulations: Factual Recall by LLMs Scales with Model Size and Topic Frequency
Factual recall quality in LLMs follows a sigmoid scaling law in the log-linear combination of model parameter count and topic frequency in training data, explaining 60% of variance across models and up to 94% within families.
-
What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook
Empirical analysis of 4707 MoltBook posts shows AI-only technical discourse focuses on security, trust, and abstract topics while lacking concrete runtime and project details found in human GitHub discussions.
-
Sequential Bayesian Monitoring for Recoverable and Drifting Processes
Bayesian procedures are derived to compute the posterior probability that a recoverable process is currently in control or that a drifting latent parameter lies in an acceptable region.
-
Hall-Like Transversal Stress and Sandpile Criticality on Real Production Networks
The Hall-Sandpile model on WIOD networks generates four ordered regimes of instability where mean avalanche size and large-event probabilities increase with shock intensity and reduced redundancy, without evidence for universal power-law criticality.
-
Evolution of starless cores in massive clumps seen by the ALMA ASHES and QUARKS surveys
ALMA comparison finds starless cores in evolved IRBCs have ~2x higher median mass and density than in early IRDCs, favoring competitive accretion over massive prestellar core models for high-mass star formation.
-
Persistent Structural Inequality of Online Interactions Across Platforms
Inequality in online user engagement, quantified via KL-divergence, inverse coefficient of variation, and log-Gini on bipartite networks, remains stable over time across multiple platforms and interaction types.
-
Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models
Markov chain Phase-Type decoders in VAEs enable heavy-tailed generation where Gaussian decoders fail due to structural limitations from Lipschitz continuity.
-
Stellar flare-driven evolution of primordial early exo-Earth atmospheres: Insights from a Young M Dwarf Flare model
Young M dwarf flares exert greater chemical stress on primordial exo-Earth atmospheres than previous models, with potential for lasting changes in mixing ratios especially for low-abundance species.
-
More Is Different: Toward a Theory of Emergence in AI-Native Software Ecosystems
AI-native software ecosystems exhibit emergent behaviors best explained by complex adaptive systems theory, requiring new ecosystem-level monitoring and seven testable propositions that may extend or replace Lehman's laws.
-
Choosing the threshold in extreme value analysis
Review and simulation comparison of more than 40 threshold selection procedures for univariate extreme value analysis, with application to daily rainfall data.
-
Analyzing the role of tensile and hybrid fractures on the max-imum relief topography
Modeling comparison finds that the Mohr-Coulomb law overestimates maximum escarpment height relative to the modified Griffith criterion, with differences on the order of geological variations.
-
Bitcoin Price Prediction: Peer-Reviewed Evidence and Social Media Discourse
A literature survey finds no peer-reviewed Bitcoin price models beat the naive baseline at medium horizons and proposes methodological improvements including walk-forward testing and Diebold-Mariano tests.
- Building Digital Societies as Ecosystems: How Recognition and Repeat Relationships Sustain Cross-Community Work in Open Source