Tootfinder

DOJ tells Republicans that Epstein files even worse for Trump than they thought: report - Alternet.org
https://www.alternet.org/doj-republicans-trump-epstein/

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Zhuofeng Li, Haoxiang Zhang, Seungju Han, Sheng Liu, Jianwen Xie, Yu Zhang, Yejin Choi, James Zou, Pan Lu
https://arxiv.org/abs/2510.05592

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a single, monolithic policy that interleaves thoughts and tool calls under full context; this scales poorly with long horizons and diverse tools and generalizes weakly to new scenarios. Agentic systems offer a promising alternative by decomposing work across specialized modules, yet most remain training-free or rely on offline training decoupled from the l…

Error analysis for learning the time-stepping operator of evolutionary PDEs
Ke Chen, Meenakshi Krishnan, Haizhao Yang
https://arxiv.org/abs/2509.04256 https://

Error analysis for learning the time-stepping operator of evolutionary PDEs
Deep neural networks (DNNs) have recently emerged as effective tools for approximating solution operators of partial differential equations (PDEs) including evolutionary problems. Classical numerical solvers for such PDEs often face challenges of balancing stability constraints and the high computational cost of iterative solvers. In contrast, DNNs offer a data-driven alternative through direct learning of time-stepping operators to achieve this balancing goal. In this work, we provide a rigoro…

Non-equilibrium Dynamics of Two-level Systems directly after Cryogenic Alternating Bias
V. Iaia, E. S. Joseph, S. Im, N. Hagopian, S. O'Kelley, C. Kim, N. Materise, S. Patra, V. Lordi, M. A. Eriksson, P. M. Voyles, K. G. Ray, Y. J. Rosen
https://arxiv.org/abs/2509.19223

UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
Akshat Dubey, Aleksandar An\v{z}el, Bahar \.Ilgen, Georges Hattab
https://arxiv.org/abs/2508.09639 https://

UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
Explainable Artificial Intelligence (XAI) techniques, such as SHapley Additive exPlanations (SHAP), have become essential tools for interpreting complex ensemble tree-based models, especially in high-stakes domains such as healthcare analytics. However, SHAP values are usually treated as point estimates, which disregards the inherent and ubiquitous uncertainty in predictive models and data. This uncertainty has two primary sources: aleatoric and epistemic. The aleatoric uncertainty, which refle…

Exploring rapidity regularization schemes at low $x$ with the DIS longitudinal structure function
Tolga Altinoluk, Guillaume Beuf, Jani Penttala
https://arxiv.org/abs/2510.08550

Exploring rapidity regularization schemes at low $x$ with the DIS longitudinal structure function
We propose three possible rapidity regulators for higher-order calculations in low $x$ QCD with gluon saturation, as alternatives to the usual lower cut-off for the integrals over the light-cone momentum $k^+$. These rapidity regulators are closely related to the $η$ regulator and to the pure rapidity regulator, which have been used primarily in studies of transverse-momentum-dependent (TMD) factorization within the soft-collinear effective theory (SCET). By choosing one of the three rapidity …