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ReclAIm: A Multi-Agent Framework for Monitoring and Correcting Performance Decline in Medical Imaging AI
Announce Type: replace Abstract: Purpose: To develop and evaluate a multi-agent framework (ReclAIm) for automated monitoring, detection, and correction of performance decline in medical image classification models. Materials and Methods: ReclAIm is a large language model-based multi-agent system that operates through natural language interaction. A master agent coordinating three task-specific agents performed performance evaluation and triggered fine-tuning when substantial performance...
Learning to Route LLMs from Implicit Cost-Performance Preferences via Meta-Learning
arXiv:2606.06178v1 Announce Type: new Abstract: Large language models (LLMs) present a trade-off between performance and cost, where more powerful models incur greater expense. LLM routing aims to mitigate expenses while maintaining performance by sending queries to the most suitable model. However, existing methods cannot perform well for different user cost-performance preferences.
Twisted stacking lets 2D conductor keep single-layer performance in bulk form
Twisted stacking lets 2D conductor keep single-layer performance in bulk form Lisa Lock Scientific Editor Robert Egan Associate Editor Two-dimensional (2D) materials, which are significantly thinner than a single sheet of paper, have long drawn attention for their exceptional performance. However, they have faced a critical limitation: Their performance degrades significantly when multiple layers are stacked. A research team led by Professor Sarah S. Park from the Department of Chemistry at...
Performative Learning Theory
arXiv:2602.04402v3 Announce Type: replace-cross Abstract: Performative predictions influence the very outcomes they aim to forecast. We study performative predictions that affect a sample (e.g., only existing users of an app) and/or the whole population (e.g., all potential app users). This raises the question of how well models generalize under performativity.
Trump mocks artists getting ‘the yips’ about his Freedom 250 concert and unveils new star performer – himself
Trump mocks artists getting ‘the yips’ about his Freedom 250 concert and unveils new star performer – himself Multiple musicians, including Bret Michaels and Martina McBride, announced this week that they would no longer perform at the concert series - Bookmark - CommentsGo to comments President Donald Trump announced Saturday he would bring the “Number One Attraction anywhere in the World” to the Freedom 250 concert series, after several notable musicians backed out of performances:...
King Charles urged to ‘get up and dance’ at Jay Sean charity gala performance
King Charles urged to ‘get up and dance’ at Jay Sean charity gala performance The singer-songwriter 45, will perform for the King at the British Asian Trust Gala on Tuesday - Bookmark - CommentsGo to comments Singer Jay Sean has expressed his hope that the King will "get up and dance" during his set at the British Asian Trust Gala this Tuesday. The 45-year-old artist, known for his 2009 hit Down with US rapper Lil Wayne, is scheduled to perform for the monarch at the annual fundraising...
From Performance to Viability: A Bootstrap Framework for Latent-Space Representation Learning in Adaptive Biological Systems
Announce Type: new Abstract: Observable performance is commonly used to characterize biological systems. In adaptive systems, however, similar performances may arise from distinct organizations, and configurations that appear comparable at a given time may follow different longitudinal trajectories. This limitation motivates a methodological framework for moving beyond performance-based interpretation without assuming a complete mechanistic model in advance.
From Roofline to Ruggedness: Decomposing and Smoothing the GEMM Performance Landscape
arXiv:2605.29752v1 Announce Type: cross Abstract: Adjacent GEMM problems that differ by a single 128-element step in N can show 30% different throughput on the same GPU. This pervasive performance ruggedness - invisible to roofline analysis and peak-FLOPs intuition, yet dominant for every non-peak workload - is the subject of this paper. We propose performance ruggedness analysis as an analytical framework complementary to roofline: rather than summarizing GPU performance with a scalar...
The Stability of Online Algorithms in Performative Prediction
Announce Type: replace Abstract: The use of algorithmic predictions in decision-making leads to a feedback loop where the models we deploy actively influence the data distributions we see, and later use to retrain on. This dynamic was formalized by Perdomo et al. 2020 in their work on performative prediction. Our main result is an unconditional reduction showing that any no-regret algorithm deployed in performative settings converges to a (mixed) performatively stable equilibrium: a solution...
Invasive and Non-Invasive Neural Decoding of Motor Performance in Parkinson's Disease for Personalized Deep Brain Stimulation
arXiv:2603.27750v2 Announce Type: replace Abstract: Decoding motor performance from brain signals offers promising avenues for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). In a two-center cohort of 19 PD patients executing a drawing task, we decoded motor performance from electroencephalography (n=15) and, critically for clinical translation, electrocorticography (n=4). Within each session, patients performed the task under DBS on and DBS off.