Tootfinder

Sound Interval-Based Synthesis for Probabilistic Programs
Guilherme Espada, Alcides Fonseca
https://arxiv.org/abs/2507.06939 https://…

Sound Interval-Based Synthesis for Probabilistic Programs
Probabilistic programming has become a standard practice to model stochastic events and learn about the behavior of nature in different scientific contexts, ranging from Genetics and Ecology to Linguistics and Psychology. However, domain practitioners (such as biologists) also need to be experts in statistics in order to select which probabilistic model is suitable for a given particular problem, relying then on probabilistic inference engines such as Stan, Pyro or Edward to fine-tune the param…

MHD Rankine-Hugoniot jump conditions for shock waves in van der Waals gases
Raj Kumar Anand
https://arxiv.org/abs/2507.07564 https://…

MHD Rankine-Hugoniot jump conditions for shock waves in van der Waals gases
In this article, we have presented non-relativistic boundary conditions across a magnetohydrodynamic (MHD) shock front propagating in van der Waals gases. The expression for the strength of the non-relativistic MHD shock wave has been obtained, and the Rankine-Hugoniot (R-H) shock jump relations, or boundary conditions, for the pressure, the density, and the particle velocity across an MHD shock front have been derived in terms of a shock compression ratio. The simplified forms of shock jump re…

Z3Guide: A Scalable, Student-Centered, and Extensible Educational Environment for Logic Modeling
Ruanqianqian Huang, Ayana Monroe, Peli de Halleux, Sorin Lerner, Nikolaj Bj{\o}rner
https://arxiv.org/abs/2506.08294

Z3Guide: A Scalable, Student-Centered, and Extensible Educational Environment for Logic Modeling
Constraint-satisfaction problems (CSPs) are ubiquitous, ranging from budgeting for grocery shopping to verifying software behavior. Logic modeling helps solve CSPs programmatically using SMT solvers. Despite its importance in many Computer Science disciplines, resources for teaching and learning logic modeling are scarce and scattered, and challenges remain in designing educational environments for logic modeling that are accessible and meet the needs of teachers and students. This paper explor…

If you took off time last week, you should check out today's Metacurity, which succinctly recaps the most critical infosec developments you might have missed, including
--IT giant Ingram Micro's systems shut down after SafePay ransomware attack
--Qantas is talking with threat actor after attack,
--Android spyware flaw exposes thousands of customers,
--Ransomware negotiator may have struck deals with hackers,
--US sanctions bulletproof hoster,
--US g…

IT giant Ingram Micro's systems shut down after SafePay ransomware attack
Qantas is talking with threat actor after attack, Android spyware flaw exposes thousands of customers, Ransomware negotiator may have struck deals with hackers, US sanctions bulletproof hoster, US goes after DRPK "IT worker" program, A racist hacked Columbia and the NYT shamed itself, much more

Workshop on authoritarianism, law, and the remaking of society
https://ift.tt/LAbVEHe
Date: 19 June 2025 to 20 June 2025 Time: 10:00 am Venue: Room S312 (Paul Webley Wing), SOAS,…
via Input 4 RELCFP

Workshop on authoritarianism, law, and the remaking of society
Date: 19 June 2025 to 20 June 2025Time: 10:00 amVenue: Room S312 (Paul Webley Wing), SOAS, University of LondonEvent type: ConferenceRegistration: The event is free to attend. Click here to register. Join us for a 2 day workshop that seeks to draw attention to the social life of laws used by authoritarian states and leaders to change the composition of societies.Download programmeScheduleRegister here to attend.

AdaDec: Uncertainty-Guided Adaptive Decoding for LLM-based Code Generation
Kaifeng He, Mingwei Liu, Chong Wang, Zike Li, Yanlin Wang, Xin Peng, Zibin Zheng
https://arxiv.org/abs/2506.08980

AdaDec: Uncertainty-Guided Adaptive Decoding for LLM-based Code Generation
Code generation with large language models (LLMs) is highly sensitive to token selection during decoding, particularly at uncertain decision points that influence program logic. While standard strategies like greedy and beam search treat all tokens uniformly, they overlook code-specific uncertainty patterns, leading to suboptimal performance. This paper presents an empirical study revealing that many generation errors stem from ranking mistakes at high-uncertainty steps, where the correct token…

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning
Shreyas Vinaya Sathyanarayana, Rahil Shah, Sharanabasava D. Hiremath, Rishikesh Panda, Rahul Jana, Riya Singh, Rida Irfan, Ashwin Murali, Bharath Ramsundar
https://arxiv.org/abs/2507.07060

DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning
Retrosynthesis, the identification of precursor molecules for a target compound, is pivotal for synthesizing complex molecules, but faces challenges in discovering novel pathways beyond predefined templates. Recent large language model (LLM) approaches to retrosynthesis have shown promise but effectively harnessing LLM reasoning capabilities for effective multi-step planning remains an open question. To address this challenge, we introduce DeepRetro, an open-source, iterative, hybrid LLM-based …

Termination Analysis of Linear-Constraint Programs
Amir M. Ben-Amram, Samir Genaim, Jo\"el Ouaknine, James Worrell
https://arxiv.org/abs/2509.06752 https://

Termination Analysis of Linear-Constraint Programs
This Survey provides an overview of techniques in termination analysis for programs with numerical variables and transitions defined by linear constraints. This subarea of program analysis is challenging due to the existence of undecidable problems, and this Survey systematically explores approaches that mitigate this inherent difficulty. These include foundational decidability results, the use of ranking functions, and disjunctive well-founded transition invariants. The Survey also discusses n…

State of the Ice Model in the IceCube Observatory
Dmitry Chirkin (for the IceCube Collaboration), Martin Rongen (for the IceCube Collaboration)
https://arxiv.org/abs/2507.06341

State of the Ice Model in the IceCube Observatory
IceCube is a neutrino observatory located at the South Pole that uses Antarctic ice as a medium for detection of Cherenkov photons. As such, analysis of the data relies on our understanding of the properties of ice within and around the instrumented volume. Over the years we have made significant progress in understanding the glacial ice and now have a comprehensive model that covers many of the relevant aspects of the photon propagation in it. In this report we give a historical overview of th…

FuzzFeed: An Automatic Approach to Weakest Precondition Generation using LLMs and Fuzzing
Daragh King, Vasileios Koutavas, Laura Kovacs
https://arxiv.org/abs/2507.05272

FuzzFeed: An Automatic Approach to Weakest Precondition Generation using LLMs and Fuzzing
The weakest precondition (WP) of a program describes the largest set of initial states from which all terminating executions of the program satisfy a given postcondition. The generation of WPs is an important task with practical applications in areas ranging from verification to run-time error checking. This paper proposes the combination of Large Language Models (LLMs) and fuzz testing for generating WPs. In pursuit of this goal, we introduce Fuzzing Guidance (FG); FG acts as a means of dire…