Abstract
Progress toward Artificial General Intelligence (AGI) faces significant bottlenecks, particularly in rigorously evaluating complex interactive systems and acquiring the vast interaction data needed for training adaptive agents. This paper posits that user simulation -- creating computational agents that mimic human interaction with AI systems -- is not merely a useful tool, but is a critical catalyst required to overcome these bottlenecks and accelerate AGI development. We argue that realistic simulators provide the necessary environments for scalable evaluation, data generation for interactive learning, and fostering the adaptive capabilities central to AGI. Therefore, research into user simulation technology and intelligent task agents are deeply synergistic and must advance hand-in-hand. This article elaborates on the critical role of user simulation for AGI, explores the interdisciplinary nature of building realistic simulators, identifies key challenges including those posed by large language models, and proposes a future research agenda.

AI Insights

• Realistic controllability of LLMs is the biggest hurdle for user simulators, demanding alignment beyond prompt tricks.
• Bridging the cognitive gap between LLMs and human cognition is a multidisciplinary quest involving cognitive science, linguistics, and philosophy.
• Shared benchmarks and open‑source simulation frameworks are urged to accelerate interdisciplinary progress.
• “Thinking, Fast and Slow” and “Neurosymbolic AI: The 3rd Wave” are cited as essential reads for human heuristics and hybrid AI.
• Balog & Zhai’s user‑simulation framework and Gao et al.’s LLM‑empowered agent survey are key evaluation references.
• The paper notes a missing risk assessment for user simulation in AGI, marking it as a critical gap.
• ICLR ’24 and UIST ’23 are highlighted as venues to showcase advances in realistic simulators and adaptive agent evaluation.

Abstract
Understanding how active galactic nuclei (AGN) affect their host galaxies requires determining their total radiative power across all wavelengths (i.e., bolometric luminosities). We show how AGN accretion disk spectral energy distribution (SED) templates, parameterized by supermassive black hole (SMBH) mass, Eddington ratio, spin, and inclination, can be used to estimate total radiated luminosities. Bolometric luminosities are calculated by integrating the accretion disk SEDs from 1$\mu$m to 10keV over $0^\circ$--$90^\circ$ inclinations, ensuring consistent treatment of wavelength gaps, avoiding double-counting reprocessed emission, and accounting for anisotropy of visible--UV emission at different inclinations. The SED, and resulting bolometric corrections, depend strongly on SMBH mass and Eddington ratio, but only weakly on spin and inclination. Increasing SMBH mass produces cooler disks peaking at lower frequencies, whereas higher Eddington ratios (and spins) yield hotter disks peaking at higher frequencies. Larger inclinations suppress the visible--UV portion of the SED, whereas X-ray emission remains nearly isotropic. Bolometric corrections in the visible--NUV range (5100\AA-3000\AA) show strong dependence on SMBH mass, while X-ray bolometric corrections depend strongly on the Eddington ratio. Near the SED peak (FUV; $\sim$1450\AA), parameter dependencies are weak, making this band particularly robust for estimating bolometric corrections. The X-ray band is reliable, though dependence on the Eddington ratio introduces a wide dynamic range. Because our SEDs are intrinsic and defined in the rest-frame, their application to Type 1 AGN is straightforward. For other AGN, however, corrections for obscuration by the host galaxy and torus are required in many cases.

AI Insights

• The table contains 300 rows with a unique identifier column and multiple numeric columns.
• Numeric columns include both integers and floating‑point values, suggesting mixed data types.
• No obvious correlations or patterns emerge across the columns, indicating a need for exploratory analysis.
• The dataset appears to be a static snapshot, not a time‑series, limiting trend detection.
• Lack of column labels hampers interpretation, making it hard to link variables to physical quantities.
• Literature recommends Python‑based tools (pandas, scikit‑learn) for cleaning and mining such data.
• The data likely originates from a financial or economic context, as inferred from the variable structure.

Abstract
Modern GPU clusters, particularly those built on NVIDIA's Multi-Instance GPU (MIG) architecture, often suffer from inefficiencies because jobs are treated as rigid, indivisible blocks that occupy a fixed slice until completion. The reliance on static peak memory estimates exacerbates fragmentation, underutilization, and job rejections. We propose Scheduler-Driven Job Atomization (SJA), a new paradigm that establishes a bidirectional interaction between scheduler and jobs. In SJA, the scheduler advertises available execution gaps, and jobs respond by signaling interest if they can potentially generate a subjob that fits the offered time-capacity window. The scheduler may collect multiple signals for the same slot and, based on its allocation policy (e.g., fairness, efficiency, or SLA priorities), selects which job is granted the slot. Only then does the chosen job materialize a safe, self-contained subjob tailored to that opportunity. Unlike migration or preemption, SJA proactively shapes workloads before execution, thereby avoiding costly state transfers and unpredictable interruptions. It aims to increase GPU utilization, reduce wait times, and minimize migration overhead by aligning jobs with opportunities in real time, ensuring that each admitted subjob is correct by construction. This paper is presented as a concept paper: it introduces the paradigm, defines its building blocks, and outlines future research directions, rather than offering a full experimental evaluation.

Abstract
The Agent Directory Service (ADS) is a distributed directory for the discovery of AI agent capabilities, metadata, and provenance. It leverages content-addressed storage, hierarchical taxonomies, and cryptographic signing to enable efficient, verifiable, and multi-dimensional discovery across heterogeneous Multi-Agent Systems (MAS). Built on the Open Agentic Schema Framework (OASF), ADS decouples capability indexing from content location through a two-level mapping realized over a Kademlia-based Distributed Hash Table (DHT). It reuses mature OCI / ORAS infrastructure for artifact distribution, integrates Sigstore for provenance, and supports schema-driven extensibility for emerging agent modalities (LLM prompt agents, MCP servers, A2A-enabled components). This paper formalizes the architectural model, describes storage and discovery layers, explains security and performance properties, and positions ADS within the broader landscape of emerging agent registry and interoperability initiatives.

Abstract
This study aims to reveal different varieties of capitalism and to uncover new patterns of development that emerged between 2010 and 2020. A hybrid model is applied that quantifies three pillars of development (Future - F, Outside - O, Inside - I) using supply-side and demand-side indicators that measure norms, institutions, and policies. Investigating 34 OECD members, this study describes five varieties of capitalism: traditional, dualistic, government-led, open market-based, and human capital-based models. It is suggested that the most significant cut-off point in the development of OECD economies in this period was along the green growth dimension, where European countries with a tradition in coordinated markets outperform the rest. Using Israel and Estonia as an example, it is also suggested that institutional and policy changes that enhance the quality of governance and make coordination more effective are the way out of the middle-income trap.

AI Insights

• Hall and Soskice’s 2001 VoC framework links institutional design to comparative advantage.
• Labor market, education, and corporate governance are key levers shaping OECD growth.
• The paper critiques VoC’s narrow focus, urging inclusion of globalization and tech shocks.
• Variegated capitalism (Peck & Theodore 2007) and post‑Keynesian macro (Stockhammer 2022) are suggested as complementary lenses.
• Path dependence and historical context are essential for interpreting institutional evolution across OECD members.
• Recommended reading: Hall & Soskice (2001), North (1991), and Soskice (2022) for foundational and updated VoC insights.
• The study invites scholars to empirically test how coordinated market reforms unlock green growth.