Model Detail
asset-harvester
—asset-harvester is an AI model released by NVIDIA. The model is registered under the image-to-3d pipeline tag on Hugging Face, distributed under a other license.
Distribution is governed by the other license — review the exact terms before commercial deployment.
asset-harvester is best fit for workloads that match the image-to-3d pipeline tag. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
AssetForge: Asset-Augmented Task Synthesis for Business Automation Agents
arXiv:2610.18330v1 Announce Type: new Abstract: Training business automation agents requires executable tasks that connect a natural-language request to an application state and a verifiable end state. Traditional Rubrics requires Authors to recreate application interfaces, initial records, policy e
ScholarStack: Layered Research Asset Orchestration and Cross-Task Reuse for Scientific Agents
arXiv:2609.23735v3 Announce Type: replace Abstract: Scientific agents support a range of literature-based research tasks, such as retrieval, question answering, evidence-grounded generation, and claim assessment. Most existing systems, however, are organized around individual tasks: the same papers
HI3D 3.0 (Twinkle3D): Object-specific 3D Asset Generation with High Resolution
arXiv:2610.11685v1 Announce Type: cross Abstract: Image-to-3D generation has become increasingly capable of producing objects that closely resemble the input image, and an outstanding challenge is to reproduce the depicted object itself, including the specific geometry that defines it. Inscriptions,
Residual Learning in Empirical Asset Pricing
arXiv:2610.09613v1 Announce Type: cross Abstract: Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existing empirical asset pricing literature provides strong benchmarks for shallow models. Residual learnin
Variance-Corrected Multi-Asset Equity Simulation with Hybrid Hidden Markov Marginals
arXiv:2603.10202v3 Announce Type: replace-cross Abstract: Synthetic multi-asset equity data must reproduce each asset's return distribution and its relationship with the market. Reusing a generator fitted to full asset returns creates a problem: adding its draws to a market factor counts market vari
Self-discovering RL in the Era of Experience: Is Learning History an Asset or a Burden?
arXiv:2609.35897v1 Announce Type: cross Abstract: The pursuit of recursive self-improvement (RSI) toward general intelligence is divided between macro-level language model scaling and the interaction-driven principles of "Era of Experience". Yet, any self-improving architecture ultimately rests upon
