Tootfinder

from my link log —
Dissolving the Fermi paradox.
https://arxiv.org/abs/1806.02404
saved 2025-04-18 https://dotat.at/:/U1H2Q.html

Dissolving the Fermi Paradox
The Fermi paradox is the conflict between an expectation of a high {\em ex ante} probability of intelligent life elsewhere in the universe and the apparently lifeless universe we in fact observe. The expectation that the universe should be teeming with intelligent life is linked to models like the Drake equation, which suggest that even if the probability of intelligent life developing at a given site is small, the sheer multitude of possible sites should nonetheless yield a large number of pot…

This https://arxiv.org/abs/2501.10639 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks
Ensuring safety alignment has become a critical requirement for large language models (LLMs), particularly given their widespread deployment in real-world applications. However, LLMs remain susceptible to jailbreak attacks, which exploit system vulnerabilities to bypass safety measures and generate harmful outputs. Although numerous defense mechanisms based on adversarial training have been proposed, a persistent challenge lies in the exacerbation of over-refusal behaviors, which compromise the…

Might I suggest that it's not only Musk's politics that are preventing people from buying Teslas, but also the slap-dash approach to road safety and crash investigation, releasing products that aren't ready, and lying at investor conferences that might also be the problem?

The Raiders Continue to Get Newest Additions Up to Speed https://www.si.com/nfl/raiders/dirk-koetter-boise-state-ashton-jeanty-las-vegas-chip-kelly

This https://arxiv.org/abs/2505.13182 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

Information Science Principles of Machine Learning: A Causal Chain Meta-Framework Based on Formalized Information Mapping
[Objective] This study focuses on addressing the current lack of a unified formal theoretical framework in machine learning, as well as the deficiencies in interpretability and ethical safety assurance. [Methods] A formal information model is first constructed, utilizing sets of well-formed formulas to explicitly define the ontological states and carrier mappings of typical components in machine learning. Learnable and processable predicates, along with learning and processing functions, are in…

This https://arxiv.org/abs/2505.23581 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum Hilbert Transform
The Hilbert transform has been one of the foundational transforms in signal processing, finding it's way into multiple disciplines from cryptography to biomedical sciences. However, there does not exist any quantum analogue for the Hilbert transform. In this work, we introduce a formulation for the quantum Hilbert transform (QHT)and apply it to a quantum steganography protocol. By bridging classical phase-shift techniques with quantum operations, QHT opens new pathways in quantum signal process…

Across the country, Republican lawmakers have been working to undermine or altogether undo the will of the voters -- by making it harder to pass amendments and laws through citizen-led initiatives.
In #Missouri, the 2025 legislative session was dominated by Republican lawmakers trying to reverse two major measures that voters had put on the ballot and approved just months before;
one made

Red State Voters Approved Progressive Measures. GOP Lawmakers Are Trying to Undermine Them.
In the wake of ballot measures that increased abortion access and improved sick leave for workers, a coordinated effort is unfolding across the country to restrict direct democracy — and shift power to partisan legislatures.

The Northern Cross Fast Radio Burst project: V. Search for transient radio emission from Galactic magnetars
A. Geminardi, P. Esposito, G. Bernardi, M. Pilia, D. Pelliciari, G. Naldi, D. Dallacasa, R. Turolla, L. Stella, F. Perini, F. Verrecchia, C. Casentini, M. Trudu, R. Lulli, A. Maccaferri, A. Magro, A. Mattana, G. Bianchi, G. Pupillo, C. Bortolotti, M. Tavani, M. Roma, M. Schiaffino, G. Setti

The Northern Cross Fast Radio Burst project: V. Search for transient radio emission from Galactic magnetars
Context. The radio emission from magnetars is poorly understood and poorly characterized observationally, in particular for what concerns single pulses and sporadic events. The interest in it was boosted by the detection in 2020 of an extremely bright ms radio signal from the Galactic magnetar designated Soft Gamma Repeater (SGR) SGR J1935+2154, which occurred almost simultaneously with a typical magnetar short burst of X-rays. As of now, this event remains the Galactic radio pulse that is the …

Can Large Language Models Trigger a Paradigm Shift in Travel Behavior Modeling? Experiences with Modeling Travel Satisfaction
Pengfei Xu, Donggen Wang
https://arxiv.org/abs/2505.23262

Can Large Language Models Trigger a Paradigm Shift in Travel Behavior Modeling? Experiences with Modeling Travel Satisfaction
As a specific domain of subjective well-being, travel satisfaction has attracted much research attention recently. Previous studies primarily use statistical models and, more recently, machine learning models to explore the determinants of travel satisfaction. Both approaches require data from sufficient sample sizes and correct prior statistical assumptions. The emergence of Large Language Models (LLMs) offers a new modeling approach that can overcome the shortcomings of the existing methods. …

Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang, Adrian Weller, Nicolas Papernot
https://arxiv.org/abs/2505.23968

Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Cautious predictions -- where a machine learning model abstains when uncertain -- are crucial for limiting harmful errors in safety-critical applications. In this work, we identify a novel threat: a dishonest institution can exploit these mechanisms to discriminate or unjustly deny services under the guise of uncertainty. We demonstrate the practicality of this threat by introducing an uncertainty-inducing attack called Mirage, which deliberately reduces confidence in targeted input regions, th…