ArgBench unifies 33 existing datasets into a standardized benchmark for testing LLMs across 46 argumentation tasks and analyzes the impact of prompting techniques and model factors on performance.
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2026 6representative citing papers
LRP on EEG transformers reveals Clever Hans artifacts in motor imagery tasks and a recurring central electrode cluster as a candidate sensorimotor signature of arousal.
GFlowNets sample multiple valid mechanistic simulator configurations for digital twin adaptation, recovering main parameter regions and preserving uncertainty in a tomato model case study.
A physics-informed neural network infers pT spectra of pi, K, p, Lambda, and Ks in unmeasured rapidity regions from PYTHIA8 pp collisions at 13.6 TeV, achieving 1.5-5.83% yield uncertainties while reproducing yield ratios and freeze-out parameters.
OrthoBO introduces an orthogonal acquisition estimator subtracting an optimally weighted score-function control variate to reduce Monte Carlo variance, preserve the acquisition target, and improve ranking stability in Bayesian hyperparameter optimization.
A quantile-regression ensemble with safety factor reduces under-allocated jobs from 4.17% to 2.89% and average overallocation from 148% to 44.51% on SAP build data.
citing papers explorer
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ArgBench: Benchmarking LLMs on Computational Argumentation Tasks
ArgBench unifies 33 existing datasets into a standardized benchmark for testing LLMs across 46 argumentation tasks and analyzes the impact of prompting techniques and model factors on performance.
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From Clever Hans to Scientific Discovery: Interpreting EEG Foundational Transformers with LRP
LRP on EEG transformers reveals Clever Hans artifacts in motor imagery tasks and a recurring central electrode cluster as a candidate sensorimotor signature of arousal.
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Generative Flow Networks for Model Adaptation in Digital Twins of Natural Systems
GFlowNets sample multiple valid mechanistic simulator configurations for digital twin adaptation, recovering main parameter regions and preserving uncertainty in a tomato model case study.
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Inferring identified hadron production in $pp$ collisions with physics-informed machine learning at the LHC
A physics-informed neural network infers pT spectra of pi, K, p, Lambda, and Ks in unmeasured rapidity regions from PYTHIA8 pp collisions at 13.6 TeV, achieving 1.5-5.83% yield uncertainties while reproducing yield ratios and freeze-out parameters.
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ORTHOBO: Orthogonal Bayesian Hyperparameter Optimization
OrthoBO introduces an orthogonal acquisition estimator subtracting an optimally weighted score-function control variate to reduce Monte Carlo variance, preserve the acquisition target, and improve ranking stability in Bayesian hyperparameter optimization.
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Optimizing Memory Allocation in Distributed Clusters with Predictive Modeling
A quantile-regression ensemble with safety factor reduces under-allocated jobs from 4.17% to 2.89% and average overallocation from 148% to 44.51% on SAP build data.