Supercomputers decode the strange behavior of Enceladus’s plumes
Cutting-edge simulations show that Enceladus’ plumes are losing 20–40% less mass than earlier estimates suggested. The new models provide sharper insights into subsurface conditions that future landers may one day probe directly.
The Second Law of Intelligence: Controlling Ethical Entropy in Autonomous Systems
arXiv:2511.10704v1 Announce Type: new Abstract: We propose that unconstrained artificial intelligence obeys a Second Law analogous to thermodynamics, where ethical entropy, defined as a measure of divergence from intended goals, increases spontaneously without continuous alignment work. For gradien
Co-EPG: A Framework for Co-Evolution of Planning and Grounding in Autonomous GUI Agents
arXiv:2511.10705v1 Announce Type: new Abstract: Graphical User Interface (GUI) task automation constitutes a critical frontier in artificial intelligence research. While effective GUI agents synergistically integrate planning and grounding capabilities, current methodologies exhibit two fundamental
Picking a Representative Set of Solutions in Multiobjective Optimization: Axioms, Algorithms, and Experiments
arXiv:2511.10716v1 Announce Type: new Abstract: Many real-world decision-making problems involve optimizing multiple objectives simultaneously, rendering the selection of the most preferred solution a non-trivial problem: All Pareto optimal solutions are viable candidates, and it is typically up to
Structure-Aware Encodings of Argumentation Properties for Clique-width
arXiv:2511.10767v1 Announce Type: new Abstract: Structural measures of graphs, such as treewidth, are central tools in computational complexity resulting in efficient algorithms when exploiting the parameter. It is even known that modern SAT solvers work efficiently on instances of small treewidth.
Potential Outcome Rankings for Counterfactual Decision Making
arXiv:2511.10776v1 Announce Type: new Abstract: Counterfactual decision-making in the face of uncertainty involves selecting the optimal action from several alternatives using causal reasoning. Decision-makers often rank expected potential outcomes (or their corresponding utility and desirability)
From Efficiency to Adaptivity: A Deeper Look at Adaptive Reasoning in Large Language Models
arXiv:2511.10788v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have made reasoning a central benchmark for evaluating intelligence. While prior surveys focus on efficiency by examining how to shorten reasoning chains or reduce computation, this view overlooks a fund
HARNESS: Human-Agent Risk Navigation and Event Safety System for Proactive Hazard Forecasting in High-Risk DOE Environments
arXiv:2511.10810v1 Announce Type: new Abstract: Operational safety at mission-critical work sites is a top priority given the complex and hazardous nature of daily tasks. This paper presents the Human-Agent Risk Navigation and Event Safety System (HARNESS), a modular AI framework designed to foreca
HyperComplEx: Adaptive Multi-Space Knowledge Graph Embeddings
arXiv:2511.10842v1 Announce Type: new Abstract: Knowledge graphs have emerged as fundamental structures for representing complex relational data across scientific and enterprise domains. However, existing embedding methods face critical limitations when modeling diverse relationship types at scale:
Advanced Tool for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction
arXiv:2511.10853v1 Announce Type: new Abstract: Traffic collision reconstruction traditionally relies on human expertise, often yielding inconsistent results when analyzing incomplete multimodal data. This study develops a multi-agent AI framework that reconstructs pre-crash scenarios and infers ve
Enhancing Demand-Oriented Regionalization with Agentic AI and Local Heterogeneous Data for Adaptation Planning
arXiv:2511.10857v1 Announce Type: new Abstract: Conventional planning units or urban regions, such as census tracts, zip codes, or neighborhoods, often do not capture the specific demands of local communities and lack the flexibility to implement effective strategies for hazard prevention or respon
LLM enhanced graph inference for long-term disease progression modelling
arXiv:2511.10890v1 Announce Type: new Abstract: Understanding the interactions between biomarkers among brain regions during neurodegenerative disease is essential for unravelling the mechanisms underlying disease progression. For example, pathophysiological models of Alzheimer's Disease (AD) typic
Multi-Agent Legal Verifier Systems for Data Transfer Planning
arXiv:2511.10925v1 Announce Type: new Abstract: Legal compliance in AI-driven data transfer planning is becoming increasingly critical under stringent privacy regulations such as the Japanese Act on the Protection of Personal Information (APPI). We propose a multi-agent legal verifier that decompos
Requirements for Aligned, Dynamic Resolution of Conflicts in Operational Constraints
arXiv:2511.10952v1 Announce Type: new Abstract: Deployed, autonomous AI systems must often evaluate multiple plausible courses of action (extended sequences of behavior) in novel or under-specified contexts. Despite extensive training, these systems will inevitably encounter scenarios where no avai
AI Agent-Driven Framework for Automated Product Knowledge Graph Construction in E-Commerce
arXiv:2511.11017v1 Announce Type: new Abstract: The rapid expansion of e-commerce platforms generates vast amounts of unstructured product data, creating significant challenges for information retrieval, recommendation systems, and data analytics. Knowledge Graphs (KGs) offer a structured, interpre
Faster Symmetry Breaking Constraints for Abstract Structures
arXiv:2511.11029v1 Announce Type: new Abstract: In constraint programming and related paradigms, a modeller specifies their problem in a modelling language for a solver to search and return its solution(s). Using high-level modelling languages such as Essence, a modeller may express their problems
Key Decision-Makers in Multi-Agent Debates: Who Holds the Power?
arXiv:2511.11040v1 Announce Type: new Abstract: Recent studies on LLM agent scaling have highlighted the potential of Multi-Agent Debate (MAD) to enhance reasoning abilities. However, the critical aspect of role allocation strategies remains underexplored. In this study, we demonstrate that allocat
Autonomous Vehicle Path Planning by Searching With Differentiable Simulation
arXiv:2511.11043v1 Announce Type: new Abstract: Planning allows an agent to safely refine its actions before executing them in the real world. In autonomous driving, this is crucial to avoid collisions and navigate in complex, dense traffic scenarios. One way to plan is to search for the best actio
ARCTraj: A Dataset and Benchmark of Human Reasoning Trajectories for Abstract Problem Solving
arXiv:2511.11079v2 Announce Type: new Abstract: We present ARCTraj, a dataset and methodological framework for modeling human reasoning through complex visual tasks in the Abstraction and Reasoning Corpus (ARC). While ARC has inspired extensive research on abstract reasoning, most existing approach
Satisficing and Optimal Generalised Planning via Goal Regression (Extended Version)
arXiv:2511.11095v1 Announce Type: new Abstract: Generalised planning (GP) refers to the task of synthesising programs that solve families of related planning problems. We introduce a novel, yet simple method for GP: given a set of training problems, for each problem, compute an optimal plan for eac