Automated judgment document generation is a significant yet challenging legal AI task. As the conclusive written instrument issued by a court, a judgment document embodies complex legal reasoning. However, existing methods often oversimplify this complex process, particularly by omitting the ``Pre-Judge'' phase, a crucial step where human judges form a preliminary conclusion. This omission leads to two core challenges: 1) the ineffective acquisition of foundational judicial elements, and 2) the inadequate modeling of the Pre-Judge process, which collectively undermine the final document's legal soundness. To address these challenges, we propose \textit{\textbf{J}udicial \textbf{U}nified \textbf{S}ynthesis \textbf{T}hrough \textbf{I}ntermediate \textbf{C}onclusion \textbf{E}mulation} (JUSTICE), a novel framework that emulates the ``Search $\rightarrow$ Pre-Judge $\rightarrow$ Write'' cognitive workflow of human judges. Specifically, it introduces the Pre-Judge stage through three dedicated components: Referential Judicial Element Retriever (RJER), Intermediate Conclusion Emulator (ICE), and Judicial Unified Synthesizer (JUS). RJER first retrieves legal articles and a precedent case
The evolution of User Interface design has emphasized the need for efficient, reusable, and editable components to ensure an efficient design process. This research introduces CoGen, a system that uses machine learning techniques to generate reusable UI components directly in Figma, one of the most popular UI design tools. Addressing gaps in current systems, CoGen focuses on creating atomic components such as buttons, labels, and input fields using structured JSON and natural language prompts. The project integrates Figma API data extraction, Seq2Seq models, and fine-tuned T5 transformers for component generation. The key results demonstrate the efficiency of the T5 model in prompt generation, with an accuracy of 98% and a BLEU score of 0.2668, which ensures the mapping of JSON to descriptive prompts. For JSON creation, CoGen achieves a success rate of up to 100% in generating simple JSON outputs for specified component types.
The sixth generation (6G) of mobile networks are being developed to overcome limitations in previous generations and meet emerging user demands. As a European project, the Smart Networks and Services Joint Undertaking (SNS JU) 6G Flagship project Hexa-X-II has a leading role for developing technologies and anchoring 6G end-to-end system. This paper summarizes the security, privacy and resilient (SPR) controls identified by Hexa-X-II project and their validation frameworks.
What happens when the strongest alliance member pressures a weaker member over territory and strategic control? We examine the Greenland sovereignty crisis as a stress test for LLM geopolitics, centered on the 2019-2026 U.S. push to acquire Greenland from the Kingdom of Denmark. The crisis nests two collective-action problems: Arctic strategic control and whether NATO can enforce alliance norms against the dominant member. We develop three games (asymmetric coercion; a NATO assurance game with a critical-mass tipping point; a triadic extensive-form game with social preferences) and test them with a multi-agent simulation in which eight frontier LLMs play six geopolitical roles (United States, Denmark, Greenland, NATO, Russia, Canada) across 3,604 completed games and 108,120 action observations. Using inverse game theory, we recover each model's structural utility parameters (alpha, beta, gamma, delta, eta) for material self-interest, reciprocity, inequality aversion, norm respect, and commitment consistency. Three findings stand out. First, all eight models become more escalatory under coercion framing (four-action escalation rises from 10.7% to 28.6%). Second, Chinese-origin model
We prove a sharp nonuniqueness result for the forced generalized SQG equation. First, this yields nonunique $\dot{H}^s$- energy solutions below the Miura-Ju class. In particular, this shows that the solutions constructed by Resnick and Marchand for the dissipative SQG equation are not necessarily unique. Second, this establishes nonuniqueness below the Ladyzhenskaya-Prodi-Serrin class for the 2D Navier-Stokes equation, as well as below the Constantin-Wu and Dong-Chen-Zhao-Liu classes for the dissipative SQG equation.
The real-time supervision of production processes is a common challenge across several industries. It targets process component monitoring and its predictive maintenance in order to ensure safety, uninterrupted production and maintain high efficiency level. The rise of advanced tools for the simulation of physical systems in addition to data-driven machine learning models offers the possibility to design numerical tools dedicated to efficient system monitoring. In that respect, the digital twin concept presents an adequate framework that proffers solution to these challenges. The main purpose of this paper is to develop such a digital twin dedicated to fault detection and diagnosis in the context of a thermal-hydraulic process supervision. Based on a numerical simulation of the system, in addition to machine learning methods, we propose different modules dedicated to process parameter change detection and their on-line estimation. The proposed fault detection and diagnosis algorithm is validated on a specific test scenario, with single one-off parameter change occurrences in the system. The numerical results show good accuracy in terms of parameter variation localization and the up
This paper proposes a comprehensive framework for the generation of covert advertisements within Conversational AI systems, along with robust techniques for their detection. It explores how subtle promotional content can be crafted within AI-generated responses and introduces methods to identify and mitigate such covert advertising strategies. For generation (Sub-Task~1), we propose a novel framework that leverages user context and query intent to produce contextually relevant advertisements. We employ advanced prompting strategies and curate paired training data to fine-tune a large language model (LLM) for enhanced stealthiness. For detection (Sub-Task~2), we explore two effective strategies: a fine-tuned CrossEncoder (\texttt{all-mpnet-base-v2}) for direct classification, and a prompt-based reformulation using a fine-tuned \texttt{DeBERTa-v3-base} model. Both approaches rely solely on the response text, ensuring practicality for real-world deployment. Experimental results show high effectiveness in both tasks, achieving a precision of 1.0 and recall of 0.71 for ad generation, and F1-scores ranging from 0.99 to 1.00 for ad detection. These results underscore the potential of our
Recent progress in driving video generation has shown significant potential for enhancing self-driving systems by providing scalable and controllable training data. Although pretrained state-of-the-art generation models, guided by 2D layout conditions (e.g., HD maps and bounding boxes), can produce photorealistic driving videos, achieving controllable multi-view videos with high 3D consistency remains a major challenge. To tackle this, we introduce a novel spatial adaptive generation framework, CoGen, which leverages advances in 3D generation to improve performance in two key aspects: (i) To ensure 3D consistency, we first generate high-quality, controllable 3D conditions that capture the geometry of driving scenes. By replacing coarse 2D conditions with these fine-grained 3D representations, our approach significantly enhances the spatial consistency of the generated videos. (ii) Additionally, we introduce a consistency adapter module to strengthen the robustness of the model to multi-condition control. The results demonstrate that this method excels in preserving geometric fidelity and visual realism, offering a reliable video generation solution for autonomous driving.
Producing high-quality code across multiple programming languages is increasingly important as today's software systems are built on heterogeneous stacks. Large language models (LLMs) have advanced the state of automated programming, yet their proficiency varies sharply between languages, especially those with limited training data such as Rust, Perl, OCaml, and Erlang. Many current solutions including language-specific fine-tuning, multi-agent orchestration, transfer learning, and intermediate-representation pipelines still approach each target language in isolation, missing opportunities to share knowledge or exploit recurring cross-language patterns. XL-CoGen tackles this challenge with a coordinated multi-agent architecture that integrates intermediate representation, code generation, translation, and automated repair. Its distinguishing feature is a data-driven mechanism for selecting bridging languages: empirically derived transfer matrices identify the best intermediate languages based on demonstrated translation success rather than raw generation accuracy. The system performs early output validation, iteratively corrects errors, and reuses intermediate artifacts as contextu
6500+ exoplanets have been detected using various techniques. This prompted the emergence of many recent works on the taxonomy, or classification, of exoplanets. However, there is still no basic, fundamental definition of 'What is a planet?'. IAU has forwarded a definition in 2006, which however, raised more questions than it solved. The first task here is to establish if there are limits on the size/mass of planets. The lower mass limit may be assumed as of Mimas (0.03 EU) - approximately minimum mass required to attain a nearly spherical hydrostatic equilibrium shape. The upper mass limit may be easier - there is a natural lower limit to what constitutes a star: 0.08 SU. But then there are brown dwarfs: IAU has defined brown dwarfs as objects exceeding the deuterium burning limit (~13 JU), and giant exoplanets generally have masses of 0.3 to 60 JU. The resolution requires assembling the basic physical parameters that define planets quantitatively. Mass and radius are the two fundamental properties, and we propose to use a third correlated parameter: the moment of inertia. Based on this, we create the parametric Fundamental Planetary Plane where the two parameters are correlated w
In this paper I focused on resource scheduling in the downlink of LTE-Advanced with aggregation of multiple Component Carriers (CCs). When Carrier Aggregation (CA) is applied, a well-designed resource scheduling scheme is essential to the LTE-A system. Joint User Scheduling (JUS), Separated Random User Scheduling (SRUS), Separated Burst-Level Scheduling (SBLS) are three different resource scheduling schemes. JUS is optimal in performance but with high complexity and not considering quality of experience (QoE) parameters. Whereas SRUS and SBLS are contrary and users will acquire few resources because they do not support CA and the system fairness is disappointing. The author propose a novel Carrier Scheduling (CS) scheme, termed as "Quality of Service and Channel Scheduling" (QSCS). Connected CCs of one user can be changed in burst level and these changes are based on checking of services priority and quality of signal that user experiences. Simulation results show that the proposed algorithm can effectively enhance throughput of users like JUS and also it chooses best CCs based on QoS and channel quality parameters. The simulation results also show that achieved QoE is much better
Researchers discovered that hydrogen radicals generated by intense UV light can break down stubborn PFAS “forever chemicals” without added chemicals。 The breakthrough reveals a key mechanism that could lead to greener and more effective technologies for permanently destroying these pollutants
The rich metadata created nowadays for objects stored in libraries has nowhere to be stored, because core standards, namely MARC 21 and Dublin Core, are not flexible enough. The aim of this paper is to summarize our work-in-progress on tackling this problem in research on cultural heritage objects at the Jagiellonian University (JU). We compared the objects' metadata currently being collected at the JU (with examples of manuscript, placard, and obituary) with five widespread metadata standards used by the cultural heritage community: Dublin Core, EAD, MODS, EDM and Digital Scriptorium. Our preliminary results showed that mapping between them is indeed problematic, but we identified requirements that should be followed in further work on the JU cultural heritage metadata schema in order to achieve maximum interoperability. As we move forward, based on the successive versions of the conceptual model, we will conduct experiments to validate the practical feasibility of these mappings and the degree to which the proposed model will actually enable integration with data in these various metadata formats.
We define and explore in-depth the notion of {\it UQ rings} by showing their important properties and by comparing their behavior with that of the well-known classes of UU rings and JU rings, respectively. Specifically, among the other established results, we prove that UQ rings are always Dedekind finite (often named directly finite) as well as that, for semipotent rings $R$, the following equivalence hold: $R/J(R)$ is UQ $\iff$ $R$ is UQ having the property that the set $QN(R)$ of quasinilpotent elements of $R$ coincides with the Jacobson radical $J(R)$ of $R$.
If you want to beef up your home security this Prime Day, Eufy’s Floodlight Camera is a great way to do it
NASA’s PExT terminal has shown that spacecraft can seamlessly communicate through multiple government and commercial networks, a major step beyond traditional single-network systems。 The mission is now expanding to test new capabilities that could help create a more flexible, reliable communications infrastructure for future space missions
Scientists discovered that kombucha’s flavor, chemistry, and antioxidant activity vary dramatically depending on the tea used to make it。 Green and oolong tea kombuchas emerged as the most biologically active, while fermentation transformed each tea into a distinctly different beverage
Oxford physicists have created an entirely new type of Schrödinger’s cat-like quantum state using components that are themselves highly quantum in nature。 The advance could open new possibilities for more resilient quantum computers and deeper insights into the strange rules that govern the quantum universe
This study presents a demonstration of the surface morphology behavior of gallium antimonide (GaSb) layers deposited on gallium arsenide (GaAs) (100) substrates using three different methods: metamorphic, interfacial misfit (IMF) matrix, and a method based on a Polish patent application number P.443805. The first two methods are commonly used, while the third differs in the sequence of successive steps and the presence of Be doping at the initial growth stage. By comparing GaSb layers made by these methods for the same growth parameters, the most favorable procedure for forming a GaSb buffer layer is selected. Using GaAs substrates with a GaSb buffer layer is a cheaper alternative to using GaSb substrates in infrared detector structures based on II-type superlattices T2SL, such as InAs/GaSb. The quality of the GaSb buffer layer determines the quality of the subsequent layers that form the entire T2SL and affects factors such as dark current in terms of application