A massive quiescent galaxy at z=3.449 exhibits low rotation (λ_Re = 0.123) consistent with slow-rotator kinematics, indicating early formation of dispersion-dominated systems.
Canonical reference
Controlling the false dis- covery rate: A practical and powerful approach to multiple testing,
Canonical reference. 71% of citing Pith papers cite this work as background.
citation-role summary
citation-polarity summary
representative citing papers
Derives heuristic coverage bounds for MLFriends nested sampling under a Binomial point process model, claiming the bias is negligible compared to statistical variance.
Generative Robust Optimisation defines uncertainty sets via neural network decoders over latent spaces and evaluates them with a five-point framework, validated on planning problems using Wasserstein autoencoders.
Uncorrected Gaussian residual penalties in full-space sampling converge after marginalization to the graph-lifted reduced posterior multiplied by the inverse absolute determinant of the state Jacobian, requiring explicit determinant corrections for equivalence.
Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
Develops a unified quadratic framework for ownership concentration with exact row/column decompositions, benchmark-adjusted dependence, multiscale aggregation, spectral characterizations, and dynamic bounds on fire-sale vulnerability and alpha variance.
Introduces Trajectory Proper Score (TPS) as a strictly proper family of trajectory-level scoring rules that elicits the complete prefix-conditioned success probability process.
The paper surveys EV charging literature through a Planning-Scheduling-Behavior framework and diagnoses a fidelity-tractability trilemma in cross-layer integration.
Analysis of 61 IO500 submissions shows four orders of magnitude score variation, strong phase correlations, and log-level file-system behaviors that aggregate scores miss.
Derives recursive Laplace transform for response time distribution in M/G/1 preemptive priority with stochastic preemption overhead and introduces job joint transform for general overhead models.
Receiving help on Stack Overflow boosts helping behavior primarily among newcomers and declines with platform tenure, based on matched difference-in-differences survival analysis of over 21 million questions.
RoMathExam supplies a century-long collection of Romanian math exams together with a new intrinsic complexity metric that correlates across frontier models at r > 0.72.
Fractional viscoelastic rough contact models reproduce logarithmic aging but erase prior memory and lack any decreasing contact area phase after unloading; this holds for all linear viscoelastic models, requiring additional local internal variables.
A simulation-based inference framework that jointly models type Ia supernovae brightness dependences, host galaxy evolution, and cosmology from photometric observations.
Acoustic features from narration show a robust association with audiobook appeal independent of title effects, based on analysis of LibriVox data and proprietary metrics.
JWST imaging reveals a z=0.92 disk galaxy with an X-shaped bulge, nuclear stellar disk, and extended disk whose bar geometry matches present-day systems, showing bar-driven secular evolution largely complete 7.6 Gyr ago.
EM algorithm for two-component exponential mixtures converges at sub-exponential rate in O(log n) iterations under generalized separation assumptions.
Proposes a six-move framework (Prime, Probe, Point, Attach, Strengthen, Test) for learning with AI, using an 'effortless' diagnostic to avoid illusion of mastery, backed by cited evidence of design-dependent outcomes including 17% harm from unguarded AI and doubled gains from engineered tutors.
Extends variable projection to constrained separable nonlinear least-squares via bilevel collapse, yielding exact reduced gradients and a convergent conditional-gradient algorithm.
Self-supervised hybrid adaptive Kalman filter learns structured corrections for data-efficient joint tracking and classification.
Simulation grounded in data from 261 students shows substantial variability in mastery learning efficiency across task-selection strategies, with targeted system constraints reducing overpractice for maladaptive strategies.
Proposes an inferential framework to test differences in categorical Gini correlations for predictor importance in classification, establishing asymptotic normality and consistency while accommodating unequal dimensions and dependence.
Stellar feedback regulates radial gas inflow in the Milky Way center, yielding time-averaged rates that fall from 5e-3 to 1e-6 solar masses per year with both smooth secular and episodic components.
Agentic reproduction of an NLP study recovers original findings and demonstrates that GPT-5.5 and Claude Opus can reduce their AI-detection probability by shrinking detector margins through 20 feedback iterations.
citing papers explorer
-
RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025)
RoMathExam supplies a century-long collection of Romanian math exams together with a new intrinsic complexity metric that correlates across frontier models at r > 0.72.
-
The Effortless Trap: Productive Struggle, AI, and the Illusion of Learning
Proposes a six-move framework (Prime, Probe, Point, Attach, Strengthen, Test) for learning with AI, using an 'effortless' diagnostic to avoid illusion of mastery, backed by cited evidence of design-dependent outcomes including 17% harm from unguarded AI and doubled gains from engineered tutors.
-
Position: Align AI to Our Aspirations, Not Our Flaws
AI alignment should target objective floors of competence, accuracy, honesty, and lawfulness rather than aggregated human preferences.
-
Building Digital Societies as Ecosystems: How Recognition and Repeat Relationships Sustain Cross-Community Work in Open Source
Cross-boundary collaboration in open source is sustained by a thin carrier layer of contributors and repeat relationships that increase pull request acceptance rates from 42% to 87%.
-
Engagement Intensity as a Learner-Modeling Signal for Adaptive AI Ethics Instruction
Self-reported LLM usage frequency associates more consistently with pre-instruction AI perceptions than prior education or self-rated familiarity in graduate trainees.