Tootfinder

Science for Peace and the need for Civil Clauses at universities and civilian research institutions
J. Altmann, U. Amaldi, M. Barone, A. Bassalat, M. Bona, J. Beullens, H. Brand, S. Brentjes, D. Britzger, J. Ellis, S. Franchoo, A. Giammanco, A. Glazov, C. Heck, H. Jung, S. Kraml, L. L\"onnblad, M. Mangano, M. Renneberg, Th. Riebe, A. Sabio-Vera, R. Sanders, J. Scheffran, M. Schmelling, T. Schucker, T. Suzuki, A. Tanasijczuk, I. Tsakov, D. Valls-Gabaud, M. Walker

Science for Peace and the need for Civil Clauses at universities and civilian research institutions
After the end of World War II, the commitment to confine scientific activities in universities and research institutions to peaceful and civilian purposes has entered, in the form of {\it Civil Clauses}, the charters of many research institutions and universities. In the wake of recent world events, the relevance and scope of such Civil Clauses has been questioned in reports issued by some governments and by the EU Commission, a development that opens the door to a possible blurring of the dist…

Recommendations for Best Practices for Data Preservation and Open Science in HEP
Simone Campana (CERN, Switzerland), Irakli Chakaberia (Lawrence Berkeley National Laboratory, USA), Gang Chen (Institute of High Energy Physics, China), Cristinel Diaconu (Centre de Physique des Particules de Marseille CPPM, France, CNRS/IN2P3 and Aix-Marseille Universit\'e, France), Caterina Doglioni (University of Manchester, UK), Dillon S. Fitzgerald (University of Michigan, USA), Vincent Garonne (B…

Recommendations for Best Practices for Data Preservation and Open Science in HEP
These recommendations are the result of reflections by scientists and experts who are, or have been, involved in the preservation of high-energy physics data. The work has been done under the umbrella of the Data Lifecycle panel of the International Committee of Future Accelerators (ICFA), drawing on the expertise of a wide range of stakeholders. A key indicator of success in the data preservation efforts is the long-term usability of the data. Experience shows that achieving this requires pr…

Lower Bounds on the Size of Markov Equivalence Classes
Erik Jahn, Frederick Eberhardt, Leonard J. Schulman
https://arxiv.org/abs/2506.20933 https://…

Lower Bounds on the Size of Markov Equivalence Classes
Causal discovery algorithms typically recover causal graphs only up to their Markov equivalence classes unless additional parametric assumptions are made. The sizes of these equivalence classes reflect the limits of what can be learned about the underlying causal graph from purely observational data. Under the assumptions of acyclicity, causal sufficiency, and a uniform model prior, Markov equivalence classes are known to be small on average. In this paper, we show that this is no longer the ca…

Microscopic and collective signatures of feature learning in neural networks
Andrea Corti, Rosalba Pacelli, Pietro Rotondo, Marco Gherardi
https://arxiv.org/abs/2508.20989 https…

Microscopic and collective signatures of feature learning in neural networks
Feature extraction - the ability to identify relevant properties of data - is a key factor underlying the success of deep learning. Yet, it has proved difficult to elucidate its nature within existing predictive theories, to the extent that there is no consensus on the very definition of feature learning. A promising hint in this direction comes from previous phenomenological observations of quasi-universal aspects in the training dynamics of neural networks, displayed by simple properties of f…

Combined machine learning for stock selection strategy based on dynamic weighting methods
Lin Cai (Department of Statistics, Columbia University, New York, USA), Zhiyang He (Department of Engineering and Informatics, University of Sussex, Brighton, UK), Caiya Zhang (Department of Statistics and Data Science, Hangzhou City University, Hangzhou, China)
https://…

Combined machine learning for stock selection strategy based on dynamic weighting methods
This paper proposes a novel stock selection strategy framework based on combined machine learning algorithms. Two types of weighting methods for three representative machine learning algorithms are developed to predict the returns of the stock selection strategy. One is static weighting based on model evaluation metrics, the other is dynamic weighting based on Information Coefficients (IC). Using CSI 300 index data, we empirically evaluate the strategy' s backtested performance and model predic…

Towards Open World Detection: A Survey
Andrei-Stefan Bulzan, Cosmin Cernazanu-Glavan
https://arxiv.org/abs/2508.16527 https://arxiv.org/pdf/2508.16527

Towards Open World Detection: A Survey
For decades, Computer Vision has aimed at enabling machines to perceive the external world. Initial limitations led to the development of highly specialized niches. As success in each task accrued and research progressed, increasingly complex perception tasks emerged. This survey charts the convergence of these tasks and, in doing so, introduces Open World Detection (OWD), an umbrella term we propose to unify class-agnostic and generally applicable detection models in the vision domain. We star…

Closure Conversion, Flat Environments, and the Complexity of Abstract Machines
Beniamino Accattoli (Inria & LIX, \'Ecole Polytechnique), Dan Ghica (Huawei Central Software Institute, University of Birmingham), Giulio Guerrieri (University of Sussex), Cl\'audio Belo Louren\c{c}o (Huawei Central Software Institute), Claudio Sacerdoti Coen (Universit\`a di Bologna)

Closure Conversion, Flat Environments, and the Complexity of Abstract Machines
Closure conversion is a program transformation at work in compilers for functional languages to turn inner functions into global ones, by building closures pairing the transformed functions with the environment of their free variables. Abstract machines rely on similar and yet different concepts of closures and environments. In this paper, we study the relationship between the two approaches. We adopt a very simple λ-calculus with tuples as source language and study abstract machines for bot…

Questions around success of Iran strikes spark fears on Capitol Hill (Mike Lillis/The Hill)
https://thehill.com/homenews/house/5369926-iran-strikes-confusion-congress/
http://www.memeorandum.com/250625/p125#a250625p125

Resolving space-time singularities in spherically symmetric black holes: geodesic completeness, curvature scalars, and tidal forces
Haroldo C. D. Lima Junior, Renan B. Magalh\~aes, Gonzalo J. Olmo, Diego Rubiera-Garcia
https://arxiv.org/abs/2506.17918

Resolving space-time singularities in spherically symmetric black holes: geodesic completeness, curvature scalars, and tidal forces
The existence of black holes in the Universe is nowadays established on the grounds of a blench of astrophysical observations, most notably those of gravitational waves from binary mergers and the imaging of supermassive objects at the heart of M87 and Milky Way galaxies. However, this success of Einstein's General Relativity~(GR) to connect theory of black holes with observations is also the source of its doom, since Penrose's theorem proves that, under physically sensible conditions, the deve…