View PDF ↗
PDF Viewer
Open Full PDF

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (68)

[1]
LLaVA-based semantic feature modulation diffusion model for underwater image enhancement
2026Guodong Fan, Shengning Zhou et al.
[2]
Beyond embedding-mapping: Social network alignment via generative information fusion and LLM-guided iterative mechanism
2026Jibing Gong, Jiquan Peng et al.
[3]
Deep-shallow semantic fusion inference based on graph neural network
2025Zhenpeng Wu, Siyang Xiao et al.
[4]
Beyond What If: Advancing Counterfactual Text Generation with Structural Causal Modeling
2024Ziao Wang, Xiaofeng Zhang et al.
[5]
CEval: A Benchmark for Evaluating Counterfactual Text Generation
2024Van Bach Nguyen, Jörg Schlötterer et al.
[6]
Copula-based transferable models for synthetic population generation
2023Pascal Jutras-Dub'e, Mohammad B. Al-Khasawneh et al.
[7]
Disentangled Representation Learning
2022Xin Wang, Hong Chen et al.
[8]
TabDDPM: Modelling Tabular Data with Diffusion Models
2022Akim Kotelnikov, Dmitry Baranchuk et al.
[9]
Generative population synthesis for joint household and individual characteristics
2022Zack Aemmer, D. MacKenzie
[10]
A Deep Generative Model for Feasible and Diverse Population Synthesis
2022Eui-Jin Kim, P. Bansal
[11]
High-Resolution Image Synthesis with Latent Diffusion Models
2021Robin Rombach, A. Blattmann et al.
[12]
On the Opportunities and Risks of Foundation Models
2021Rishi Bommasani, Drew A. Hudson et al.
[13]
Counterfactual explanations as interventions in latent space
2021Riccardo Crupi, Alessandro Castelnovo et al.
[14]
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction
2021Shauli Ravfogel, Grusha Prasad et al.
[15]
Conditional Image Generation by Conditioning Variational Auto-Encoders
2021William Harvey, Saeid Naderiparizi et al.
[16]
Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text
2020Nishtha Madaan, Inkit Padhi et al.
[17]
Population synthesis for urban resident modeling using deep generative models
2020M. Johnsen, Oliver Brandt et al.
[18]
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
2020Sahil Verma, Varich Boonsanong et al.
[19]
A Survey of Knowledge-enhanced Text Generation
2020W. Yu, Wenhao Yu et al.
[20]
Variational Autoencoder with Learned Latent Structure
2020Marissa Connor, Gregory H. Canal et al.

Showing 20 of 68 references

Founder's Pitch

"SemaPop offers semantic-statistical population synthesis using LLMs to enhance generative performance in socio-economic simulations."

Generative ModelsScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

3/4 signals

7.5

Series A Potential

1/4 signals

2.5

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 2/12/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.